bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anti-α-1,4-D-polygalacturonic acid antibodies as a new biomarker for juvenile idiopathic arthritis
Authors: Huang Jiqian , Wu Zhijing , Quan Wei , Ye Xiaohua , Dai Xiaolong , Luo Jiangtao , Han Xiao , Li Xiaozhong , Zheng Wenjie 
Published: July 2024

Abstract
Objective
Diagnosing juvenile idiopathic arthritis (JIA) is challenging. Our study aimed to investigate the clinical significance of anti-α-1,4-D-polygalacturonic acid (PGA) antibodies in JIA, focusing on their role in diagnosis and assessing disease activity.

Methods
In this prospective case–control study, we examined variations in serum levels of PGA-IgA and PGA-IgG among children with different types of JIA and healthy controls. Serum PGA-IgA and PGA-IgG levels were assessed concurrently in children with active and inactive JIA.

Results
This study included 126 patients diagnosed with JIA, 13 neonates, and 76 healthy children. Serum PGA-IgA and PGA-IgG levels were assessed, which revealed significant differences in PGA-IgA levels between various JIA subtypes and controls. An analysis of PGA-IgA levels in various JIA states revealed a statistically significant difference. Receiver operating characteristic (ROC) analysis demonstrated the robust predictive capability of PGA-IgA, with an AUC of 0.879 (p < 0.001), along with a specificity of 0.842 and sensitivity of 0.848.

Conclusion
Increased levels of anti-PGA antibodies, particularly PGA-IgA, were significantly associated with JIA. PGA-IgA may serve as a sensitive biomarker for disease activity in JIA and could potentially aid in the diagnosis of JIA.

Key Points• This study found a significant correlation between blood levels of PGA-IgA and juvenile idiopathic arthritis (JIA), which may provide valuable diagnostic insights.• PGA-IgA shows potential as a sensitive biomarker for the assessment of disease activity in JIA patients, helping to determine disease activity.
Efficacy and safety of glucocorticoids in the treatment of COVID-19: a systematic review and meta-analysis of RCTs
Authors: Ye Xiangrong , Li Ye , Luo Feng , Xu Zhibin , Kasimu Kaidirina , Wang Juan , Xu Peihang , Tan Chunjiang , Yi Hui , Luo Yifeng 
Published: July 2024

AbstractIn the realm of acute respiratory infections, coronavirus disease-19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a global public health challenge. The application of corticosteroids (CSs) in COVID-19 remains a contentious topic among researchers. Accordingly, our team performed a comprehensive meta-analysis of randomized controlled trials (RCTs) to meticulously evaluate the safety and efficacy of CSs in hospitalized COVID-19 patients. To explore efficacy of CSs in the treatment of COVID-19 patients, we meticulously screened RCTs across key databases, including PubMed, Web of Science, Embase, Cochrane Library, ClinicalTrials.gov, as well as China's CNKI and Wanfang Data. We focused on assessing the 28 days mortality rates. We evaluated the data heterogeneity using the Chi-square test and I2 values, setting significance at 0.1 and 50%. Data from 21 RCTs involving 5721 participants were analyzed. The analysis did not demonstrate a significant association between CSs intervention and the 28 days mortality risk in hospitalized COVID-19 patients (relative risk [RR] = 0.93; 95% confidence interval [95% CI]: 0.84–1.03; P = 0.15). However, subgroup analysis revealed a significant reduction in 28 days mortality among patients with moderate-to-severe COVID-19 (RR at 0.85; 95% CI: 0.76–0.95; P = 0.004). Specifically, short-term CS administration (≤ 3 days) was associated with a substantial improvement in clinical outcomes (RR = 0.24; 95% CI: 0.09–0.63; P = 0.004), as was longer-term use (≥ 8 days) (RR = 0.88; 95% CI: 0.77–0.99; P = 0.04). Additionally, in patients with moderate-to-severe COVID-19, the administration of dexamethasone increased the number of 28 days ventilator-free days (Mean Difference = 1.92; 95% CI: 0.44–3.40; P = 0.01). Methylprednisolone also demonstrated significant benefits in improving clinical outcomes (RR = 0.24; 95% CI: 0.09–0.63; P = 0.004). Our meta-analysis demonstrated that although there is no significant difference in 28 days mortality rates among hospitalized COVID-19 patients, the use of CSs may be beneficial in improving clinical outcomes in moderate or severe COVID-19 patients. There was no significant increase in the occurrence of adverse events associated with the use of CSs. Our meta-analysis provides evidence that while CSs may not be suitable for all COVID-19 patients, they could be effective and safe in severely ill COVID-19 patients. Consequently, it is recommended to administer CSs for personalized treatments in COVID-19 cases to improve the clinical outcomes while minimizing adverse events.
An update to experimental and clinical aspects of tumor-associated macrophages in cancer development: hopes and pitfalls
Authors: Salmaninejad Arash , Layeghi Sepideh Mehrpour , Falakian Zeinab , Golestani Shahin , Kobravi Sepehr , Talebi Samaneh , Yousefi Meysam 
Published: July 2024

AbstractTumor-associated macrophages (TAMs) represent one of the most abundant tumor-infiltrating stromal cells, and their normal function in tumor microenvironment (TME) is to suppress tumor cells by producing cytokines which trigger both direct cell cytotoxicity and antibody-mediated immune response. However, upon prolonged exposure to TME, the classical function of these so-called M1-type TAMs can be converted to another type, “M2-type,” which are recruited by tumor cells so that they promote tumor growth and metastasis. This is the reason why the accumulation of TAMs in TME is correlated with poor prognosis in cancer patients. Both M1- and M2-types have high degree of plasticity, and M2-type cells can be reprogrammed to M1-type for therapeutic purposes. This characteristic introduces TAMs as promising target for developing novel cancer treatments. In addition, inhibition of M2-type cells and blocking their recruitment in TME, as well as their depletion by inducing apoptosis, are other approaches for effective immunotherapy of cancer. In this review, we summarize the potential of TAMs to be targeted for cancer immunotherapy and provide an up-to-date about novel strategies for targeting TAMs.
Novel Vpx virus-like particles to improve cytarabine treatment response against acute myeloid leukemia
Authors: Nair Ramya , Salinas-Illarena Alejandro , Sponheimer Monika , Wullkopf Inès , Schreiber Yannick , Côrte-Real João Vasco , del Pozo Ben Augusto , Marterer Helena , Thomas Dominique , Geisslinger Gerd , Cinatl Jindrich , Subklewe Marion , Baldauf Hanna-Mari 
Published: July 2024

AbstractKnowledge of the molecular pathogenesis of acute myeloid leukemia has advanced in recent years. Despite novel treatment options, acute myeloid leukemia remains a survival challenge for elderly patients. We have recently shown that the triphosphohydrolase SAMHD1 is one of the factors determining resistance to Ara-C treatment. Here, we designed and tested novel and simpler virus-like particles incorporating the lentiviral protein Vpx to efficiently and transiently degrade SAMHD1 and increase the efficacy of Ara-C treatment. The addition of minute amounts of lentiviral Rev protein during production enhanced the generation of virus-like particles. In addition, we found that our 2nd generation of virus-like particles efficiently targeted and degraded SAMHD1 in AML cell lines with high levels of SAMHD1, thereby increasing Ara-CTP levels and response to Ara-C treatment. Primary AML blasts were generally less responsive to VLP treatment. In summary, we have been able to generate novel and simpler virus-like particles that can efficiently deliver Vpx to target cells.
Signal drift in diffusion MRI of the brain: effects on intravoxel incoherent motion parameter estimates
Authors: Jalnefjord Oscar , Rosenqvist Louise , Warsame Amina , Björkman-Burtscher Isabella M. 
Published: July 2024

Abstract
Objectives
Signal drift has been put forward as one of the fundamental confounding factors in diffusion MRI (dMRI) of the brain. This study characterizes signal drift in dMRI of the brain, evaluates correction methods, and exemplifies its impact on parameter estimation for three intravoxel incoherent motion (IVIM) protocols.

Materials and methods
dMRI of the brain was acquired in ten healthy subjects using protocols designed to enable retrospective characterization and correction of signal drift. All scans were acquired twice for repeatability analysis. Three temporal polynomial correction methods were evaluated: (1) global, (2) voxelwise, and (3) spatiotemporal. Effects of acquisition order were simulated using estimated drift fields.

Results
Signal drift was around 2% per 5 min in the brain as a whole, but reached above 5% per 5 min in the frontal regions. Only correction methods taking spatially varying signal drift into account could achieve effective corrections. Altered acquisition order introduced both systematic changes and differences in repeatability in the presence of signal drift.

Discussion
Signal drift in dMRI of the brain was found to be spatially varying, calling for correction methods taking this into account. Without proper corrections, choice of protocol can affect dMRI parameter estimates and their repeatability.
Home range overlaps of the brushtail possum (Trichosurus vulpecula): implications for disease transmission
Authors: Tobajas Jorge , Richardson Kyle S. , French Nigel P. , Buddle Bryce , Jewell Christopher , Tompkins Daniel M. , Rouco Carlos 
Published: July 2024

AbstractUnderstanding how bovine tuberculosis (TB) is maintained in wildlife reservoirs is critical for the management of this disease impacting cattle in many countries. For the primary wildlife reservoir of the disease in New Zealand, the brushtail possum (Trichosurus vulpecula), transmission of this contagious bacterial disease among possums is often assumed to be linked to home range overlap. Identifying drivers of possum home range, and home range overlap between individuals, is thus important for informing wildlife reservoir TB management in New Zealand. We monitored four sub-populations of free-living possums in New Zealand native forests during 10 consecutive months using live trapping, to give the first direct insight into how the frequency and area of overlaps alters with density, sex and age. A total of 832 individuals were captured (average 9.3, range from 1 to 40 captures per animal with a median value of 7) and 35,820 home range overlaps were recorded. Both the number and area of overlaps were significantly associated with age class, with 66.6% of overlaps occurring between adults, 30% between adults and juveniles, and only 3.4% between juveniles. Overall, adult males showed significantly higher numbers of overlaps than expected, while adult and juvenile females showed significantly lower numbers of overlaps than expected and no differences were observed in juvenile males. In addition, males exhibited more and larger overlaps than females. The number and size of overlaps per individual decreased with increasing local population density. Understanding shared areas of activity among individuals can provide insights into the interactions occurring and potential pathways for diseases transmitted by contact such as TB. These results can inform to develop effective strategies for the control of diseases carried and dispersed by possums.
Efficacy and safety of topical azithromycin therapy in patients with blepharitis and meibomian gland dysfunction
Authors: Shimazaki Jun , Kito Gakushi , Kamoi Mizuka , Satake Yoshiyuki 
Published: July 2024

Abstract
Purpose
To assess the effects of 1% azithromycin ophthalmic solution (AZM) in patients with bacterial blepharitis accompanied by meibomian gland dysfunction (MGD).

Study design
A multicenter, single arm, prospective interventional study.

Methods
AZM was administered to the affected eyes twice daily for the first 2 days and once daily for the subsequent 12 days. Lid margin hyperaemia/redness, collarette at the root of the eyelashes, conjunctival hyperaemia, foreign body sensation, and epiphora were assessed on Days 1, 14, and 28. The Dry Eye-related Quality of Life Score (DEQS) and objectives related to MGD, including lid vascularity, lid margin irregularity, foaming, lid plugging, keratoconjunctival disorders, Marx line, meibum grade, and tear breakup time, were also assessed. Bacterial culture of the conjunctival sac and meibum was performed on Days 1 and 14.

Results
Twenty-four eyes of 24 patients (10 men/14 women, mean age 72.3 ± 13.2) were included. On Days 14 and 28, the total score, lid vascularity, lid plugging, and meibum grade showed significant improvement (p < 0.05). On Day 1, 71 strains were isolated from 22 of the 24 eyes (91.7%). Cutibacterium acnes, Corynebacterium spp., and Staphylococci were detected at high frequencies. The overall disappearance rates of the bacteria in the conjunctival sac and meibum at the end of treatment were 65.7% and 58.3%, respectively. No serious ocular or systemic adverse events were observed.

Conclusion
Fourteen-day treatment with AZM was effective in patients with blepharitis accompanied by MGD, and the efficacy of AZM persisted for a period after the treatment.
When is it acceptable to break the rules? Knowledge representation of moral judgements based on empirical data
Authors: Awad Edmond , Levine Sydney , Loreggia Andrea , Mattei Nicholas , Rahwan Iyad , Rossi Francesca , Talamadupula Kartik , Tenenbaum Joshua , Kleiman-Weiner Max 
Published: July 2024

AbstractConstraining the actions of AI systems is one promising way to ensure that these systems behave in a way that is morally acceptable to humans. But constraints alone come with drawbacks as in many AI systems, they are not flexible. If these constraints are too rigid, they can preclude actions that are actually acceptable in certain, contextual situations. Humans, on the other hand, can often decide when a simple and seemingly inflexible rule should actually be overridden based on the context. In this paper, we empirically investigate the way humans make these contextual moral judgements, with the goal of building AI systems that understand when to follow and when to override constraints. We propose a novel and general preference-based graphical model that captures a modification of standard dual process theories of moral judgment. We then detail the design, implementation, and results of a study of human participants who judge whether it is acceptable to break a well-established rule: no cutting in line. We then develop an instance of our model and compare its performance to that of standard machine learning approaches on the task of predicting the behavior of human participants in the study, showing that our preference-based approach more accurately captures the judgments of human decision-makers. It also provides a flexible method to model the relationship between variables for moral decision-making tasks that can be generalized to other settings.
SRGAN-enhanced unsafe operation detection and classification of heavy construction machinery using cascade learning
Authors: Kim Bubryur , An Eui-Jung , Kim Sungho , Sri Preethaa K. R. , Lee Dong-Eun , Lukacs R. R. 
Published: July 2024

AbstractIn the inherently hazardous construction industry, where injuries are frequent, the unsafe operation of heavy construction machinery significantly contributes to the injury and accident rates. To reduce these risks, this study introduces a novel framework for detecting and classifying these unsafe operations for five types of construction machinery. Utilizing a cascade learning architecture, the approach employs a Super-Resolution Generative Adversarial Network (SRGAN), Real-Time Detection Transformers (RT-DETR), self-DIstillation with NO labels (DINOv2), and Dilated Neighborhood Attention Transformer (DiNAT) models. The study focuses on enhancing the detection and classification of unsafe operations in construction machinery through upscaling low-resolution surveillance footage and creating detailed high-resolution inputs for the RT-DETR model. This enhancement, by leveraging temporal information, significantly improves object detection and classification accuracy. The performance of the cascaded pipeline yielded an average detection and first-level classification precision of 96%, a second-level classification accuracy of 98.83%, and a third-level classification accuracy of 98.25%, among other metrics. The cascaded integration of these models presents a well-rounded solution for near-real-time surveillance in dynamic construction environments, advancing surveillance technologies and significantly contributing to safety management within the industry.
Exploring the long-term impact of a cadmium pollution accident on microbial communities in river ecosystems
Authors: Wang Min , Wang Yuannan , Wu Yanli , Ma Qianli , Huang Jilin , He Tao , Huang Shan , Chen Chen 
Published: July 2024

AbstractThe large leakage accidents of heavy metals from industrial facilities pose a serious environmental problem; however, not enough studies have been conducted to assess the long-term ecological risk associated with such accidents. This study evaluated changes in the bacterial communities within river sediment and identified the key functional microorganisms responding to the 2012 cadmium contamination incident in the Long River, Guangxi Province, China. Results revealed that after a prolonged period of pollution accidents, cadmium pollution still had a discernible effect on the bacterial communities of the river sediment. In comparison to the control site (S1), the bacterial α-diversity in sediments from the accident area (S3) and its downstream (S5) showed a significant increase following the incident. In the control site, Burkholderiaceae was dominant, while in S3 and S5, Pedosphaeraceae, Nitrosomonadaceae, Nitrospiraceae and Geobacteraceae were significantly increased. Sulfur bacteria were found to be more responsive to this cadmium contamination than other bacteria. At site S3, the abundances of Sulfuricurvum, Sulfurifustis, Thioalkalispira, Desulfobacteraceae and Desulfarculaceae were hundreds of times higher than at site S1, indicating an intensification of sulfur cycling processes. The functional prediction implied that cadmium pollution may promote methane oxidation coupled with sulfate reduction reactions and altered the processes of nitrification and denitrification. Environmental factors influencing the microbial community included the levels of metals (cadmium, arsenic, iron) in sediment, as well as other sediment characteristics like temperature and electrical conductivity. These findings contribute to our understanding of the long-term ecological consequences of environmental pollution in river ecosystems.
Graphical abstract
A robust second-order low-rank BUG integrator based on the midpoint rule
Authors: Ceruti Gianluca , Einkemmer Lukas , Kusch Jonas , Lubich Christian 
Published: July 2024

AbstractDynamical low-rank approximation has become a valuable tool to perform an on-the-fly model order reduction for prohibitively large matrix differential equations. A core ingredient is the construction of integrators that are robust to the presence of small singular values and the resulting large time derivatives of the orthogonal factors in the low-rank matrix representation. Recently, the robust basis-update & Galerkin (BUG) class of integrators has been introduced. These methods require no steps that evolve the solution backward in time, often have favourable structure-preserving properties, and allow for parallel time-updates of the low-rank factors. The BUG framework is flexible enough to allow for adaptations to these and further requirements. However, the BUG methods presented so far have only first-order robust error bounds. This work proposes a second-order BUG integrator for dynamical low-rank approximation based on the midpoint quadrature rule. The integrator first performs a half-step with a first-order BUG integrator, followed by a Galerkin update with a suitably augmented basis. We prove a robust second-order error bound which in addition shows an improved dependence on the normal component of the vector field. These rigorous results are illustrated and complemented by a number of numerical experiments.
Legitimating Organizational Secrecy
Authors: Clarke Nicholas , Higgs Malcolm , Garavan Thomas 
Published: July 2024

Abstract
This paper brings into focus the concept of organizational secrecy by senior managers in the context of a major strategic change program. Underpinned by legitimation theory and utilizing a narrative methodology and a longitudinal investigation, we draw upon data from 52 interviews with 13 senior managers conducted at 3 months intervals over the course of 12 months. Our findings reveal that senior managers utilized seven discursive legitimation strategies to justify keeping secret that the organization intended to downsize, and they used a different mix of legitimation strategies as the change process evolved. We labeled these discursive legitimation strategies as (1) Naturalization, (2) Rationalization, (3) Moralization, (4) Authorization, (5) Proceduralization, (6) Valorization, and (7) Demonization. Theoretically we bring a temporal perspective to understanding organizational secrecy and the central role that discursive legitimation plays. We show that the use of these discursive legitimation strategies are anchored to meta-narratives describing work practices and values associated with the organization’s culture. And that managers use discursive legitimation to manage the ethical implications of secrecy.
Poietic symbiosis or algorithmic subjugation: generative AI technology in marketing communications education
Authors: Karimova Gulnara Z. , Kim Yevgeniya D. , Shirkhanbeik Amir 
Published: July 2024

Abstract
This exploratory study investigates the convergence of marketing communications and AI-powered technology in higher education, adopting a perspective on student interactions with generative AI tools. Through a comprehensive content analysis of learners’ responses, we employed a blend of manual scrutiny, Python-generated Word Cloud, and Latent Dirichlet Allocation (LDA) to expose the nature of interaction between learners and AI tools. Our findings indicate that learners predominantly adhere to the perception of AI as a tool resembling a ‘brush’ in the creative process, rather than as an active co-creator – the percaption that is aligned with the conventional tool-user dynamic. Students articulated a dual narrative regarding AI: they acknowledged its utility in enhancing creativity, yet expressed concerns about overreliance potentially eroding their own creative skills. Heidegger’s exploration of different modes of ‘revealing’ and Deleuze and Guattari’s notions of desiring machines and machinic enslavement suggest an alternative perspective where technology, and by extension AI-empowered technology, can contribute to a deeper existential understanding. This study points out the possibility of moving beyond a simple tool-user model, suggesting the emergence of more complex plausible scenarios of interaction: poietic symbiosis or algorithmic subjugation.