bluuebunny/crossref_metadata_2025 huggingface dataset:
Lethal model for respiratory syncytial virus infection using C57BL/6 mice
Authors: Takahashi Tatsuki , Amarbayasgalan Sodbayasgalan , Ueno Shiori , Sugiura Yoshiro , Dorjsuren Enkhjin , Shimizu Kenta , Kamitani Wataru
Published: November 2024

Respiratory syncytial virus (RSV) infection is a major infectious disease affecting public health. Infants and elderly infected with RSV can develop severe respiratory symptoms. A mouse model mimicking human RSV infection could be useful in elucidating the pathogenesis of RSV. However, previous mouse models did not adequately mimic the pathophysiology of human patients. We attempted to establish a new mouse-adapted RSV strain via serial passaging of mice. We rescued the MP11 virus (which had one non-synonymous substitution in each of the F, G, and L genes) through serial passaging in mice. The MP11 virus was inoculated into mice to evaluate whether it had adapted to the mouse. Viral RNA levels in the lungs of 25-week-old mice infected with MP11 virus were higher than those in the lungs of mice infected with A2 virus. There was a high infiltration of inflammatory cells and high expression of several inflammatory cytokines (IFN-γ, CCL2, TNF-α, and IL-6) in the MP11 virus-infected lungs. Furthermore, the MP11 virus can also cause lethal pneumonia in mice via high-concentration inoculation. These results indicated that the MP11 virus is a more mouse-adapted strain than the A2 virus. We generated a recombinant MP11 virus (rMP11) using reverse genetics. The rMP11 virus could grow in the lungs of mice, similar to the parent MP11 virus. In conclusion, we successfully established a new mouse-adapted strain, MP11, and reverse genetics for this strain. These MP11 and rMP11 viruses could contribute to mouse experiments aimed at elucidating RSV pathogenesis.

IMPORTANCE

A mouse model of respiratory syncytial virus (RSV) infection is useful for fundamental research aimed at developing antiviral drugs. Previous mouse models of RSV infection were unable to adequately mimic the pathophysiology of human patients due to the low amplification efficiency of this virus in the mouse lung. Furthermore, mice other than BALB/C mice are difficult to use for the RSV infectious model. We established a new mouse-adapted RSV strain, MP11. The MP11 virus can cause severe pneumonia in C57BL/6 mice and efficiently replicate and induce inflammation in the lung. Therefore, C57BL/6 mice can be used for RSV infection experiments using MP11 virus. We established a reverse genetics system for the MP11 virus using our mouse model. This system enables detailed analyses of the MP11 virus, such as functional analysis of each viral protein. Our study provides techniques that can advance fundamental research in elucidating the pathogenesis of RSV infections.
Genome sequences of
Microvirga
spp. CF3062 and CF3016 isolated from nodules found on herbarium specimens collected in 2004 and 2015
Authors: Petipas Renee H. , Kehlet-Delgado Hanna , Antoch Amanda A. , Friesen Maren L.
Published: November 2024

We present the genomes of two
Microvirga
isolates isolated from nodules found on
Medicago lupulina
herbarium specimens at the Marion Ownbey Herbarium at Washington State University. These genomes and others from herbarium specimens offer an unprecedented opportunity to study the bacterial evolution of plant-associated microbes over long time scales.
Geochemical evidence for terrigenous sediment recycling in the Late Permian subcontinental lithospheric mantle of the northern North China Craton
Authors: Wang Zhigang , Dai Li-Qun , Zhao Zi-Fu , Fang Wei
Published: November 2024

Understanding the recycling process of subducted slab in subduction zones is vital to deciphering the heterogeneity of cratonic mantle and the variable compositions of continental arc igneous rocks. This study presents a comprehensive analysis of zircon U-Pb ages, Hf-O isotopes, hornblende major elements, whole-rock major and trace elements, as well as Sr-Nd-Hf isotopes of mafic igneous rocks from the northern North China Craton. These data constrain metasomatic processes in the cratonic mantle. The Late Permian mafic igneous rocks (ca. 254–252 Ma) studied are characterized by arc-like trace element signatures and enriched whole-rock Sr-Nd-Hf isotopes, with (87Sr/86Sr)i ratios of 0.7063–0.7076, εNd(t) values of −18.0 to −9.3, and εHf(t) values of −29.7 to +0.5. In addition, they also have elevated zircon δ18O values of 5.9‰–7.0‰, and variable zircon εHf(t) values of −19.4 to +6.0. These features suggest the rocks were derived from an enriched mantle with the involvement of terrigenous sediments. We propose that the subcontinental lithospheric mantle of the northern North China Craton was mainly metasomatized by terrigenous sediment-derived hydrous melt during the southward subduction of the Paleo-Asian Ocean. Moreover, partial melting of the metasomatic mantle may be triggered by the slab rollback related to the closure of the Paleo-Asian Ocean in the Late Permian, which resulted in the formation of the mafic igneous rocks studied. Thus, the Late Permian igneous rocks studied provide petrological and geochemical evidence of the crust-mantle interaction during the subduction of the Paleo-Asian Ocean.
Supplemental Material: Throw distribution across the Dabbahu–Manda Hararo dike-induced fault array: Implications for rifting and faulting
Authors: Hofmann Barbara , al. et
Published: November 2024

 We provide a version of Figure 2 without interpretations to better view the data used. There is also a text file describing further detail of the datasets and methods used and an associated figure showing the ALOS interferogram of ground deformation associated with the October 2008 diking event.  
Intra-arterial contrast administration: a confounding appearance on stroke CT imaging
Authors: Fallon Matthew , Johnson Declan
Published: November 2024

A female patient in her 70s presented with mild slurred speech. Clinical assessment revealed only minor dysarthria. A stroke protocol CT study was performed comprising a non-contrast CT head, CT angiogram (CTA) and CT perfusion (CTP) imaging. Despite a normal non-contrast CT head, CTP imaging demonstrated a large left anterior circulation territory abnormality compatible with core infarct. The CTA displayed absent left middle cerebral artery opacification and an abnormal pattern of thalamic and posterior fossa structure enhancement. Following a neuroradiology review, it was identified that the contrast bolus had been administered into the right brachial artery causing direct arterial opacification of the right vertebral/carotid arteries and their distal branches. No contrast was present in the left carotids or distal left intracranial anterior circulation giving the false impression of a large vessel occlusion. The patient was subsequently discharged without receiving inappropriate reperfusion therapy. This case highlights the role of technical factors influencing CT interpretation, particularly when performed by artificial intelligence/automated analysis.
Association of self-reported health problems and interpersonal violence in sport: a cross-sectional study in world-level performing athletes
Authors: Mountjoy Margo , Adriaens Karolien , Junge Astrid , Verhelle Helena , Laureys Felien , Kirby Sandi , Dienstbach-Wech Lenka , Foster Jeremy , Vertommen Tine
Published: November 2024

Objectives

A paucity of studies assesses the intersection of physical health (injury and illness), mental health and experiences of interpersonal violence (IV, also known as harassment and abuse) in sport. The objectives of this study were to examine the (a) frequency of self-reported physical and mental health problems of elite athletes in the 12 months prior to the survey, (b) differences in physical and mental health between male and female athletes and (c) relationship of athlete health with experiences of IV.

Methods

Elite adult athletes from four sports were approached at eight international events to answer an online questionnaire on their physical and mental health, as well as experiences of IV in sport within the past 12 months.

Results

A total of 562 athletes completed the questionnaire. Overall, 75% reported at least one physical symptom, most commonly headache and fatigue (n=188; 33.5% each), followed by musculoskeletal symptoms (n=169; 29.4%). 65.1% reported at least one mental health symptom, mostly of anxiety or depression. More female than male athletes reported physical (F:81.9%; M:68.3%; p<0.001) and mental (F:71.9%; M:58.4%; p<0.001) health problems, while addiction problems were more frequent in male athletes (F:1.8%; M:6.4%; p=0.006. 53.0% of the female and 42.3% of the male participants reported having experienced at least one form of IV. Linear regression analysis demonstrated that all forms of IV, except physical IV (all p’s<0.001), were associated with an increasing number of physical and mental health symptoms. In addition, the analysis showed that female athletes had a higher increase in symptoms in response to IV than male athletes.

Conclusions

This study demonstrates the relationship of elite athlete physical and mental health with IV. Injury and illness prevention programmes in international sport should include strategies to reduce IV.
Shifting official development assistance during COVID-19: earmarking, donor concentration and loans
Authors: Woskie Liana , Wenham Clare
Published: November 2024

Context

In contrast to bilateral aid, aid disbursed from multilateral institutions increased significantly at the onset of the COVID-19 pandemic. Yet, at a time when a coherent and effective multilateral response is needed most, the COVID-19 pandemic revealed a shifting landscape of donor agencies that struggle with basic functions, such as cross-national coordination. While multilaterals are uniquely positioned to transcend national priorities and respond to pandemics, functionally we find official development assistance (ODA) from these entities may increasingly mimic the attributes of bilateral aid. We explore three important, but not comprehensive, attributes of aid leading up to and during the COVID-19 pandemic: (1) earmarking, (2) donor concentration and (3) aid modality.

Methods

We examine ODA disbursements over time in 2020 constant prices from 2010 to 2021 and plot share of inflow that is earmarked against each United Nations multilateral against their average annual financing volume. We then assess market diversity with two measures: the Shannon-Weiner Function and Gini-Simpson Index. Finally, we examine financing vehicles used to disburse and look at ‘grant share’ of total ODA from all formal donors over time.

Findings

We find that while the absolute number of formal multilateral actors and market diversity have been increasing since 2011, there has been a concurrent market consolidation led by the World Bank Group at 37% of market share in 2021. This coincides with an increasing prevalence of earmarking of aid inflows to the multilateral system and, unique to multilaterals but concerning given increasing debt risk, a rise in loan-based ODA disbursements.

Conclusions

In theory, this consolidation may streamline revenue pooling and allow for a more collective approach to mitigating pandemic risk but, paired with increased earmarking, has the potential to sideline both collective goals (eg, the Sustainable Development Goals) and counties’ core mandates (such as the pursuit of universal health coverage).
What CPAP to use in the delivery room? Bench comparison of two methods to provide continuous positive airways pressure in neonates
Authors: Gruber Viktoria , Tracy Mark Brian , Hinder Murray Kenneth , Morakeas Stephanie , Dronavalli Mithilesh , Drevhammar Thomas
Published: November 2024

Background

Continuous positive airway pressure (CPAP) is a recommended first-line therapy for infants with respiratory distress at birth. Resuscitation devices incorporating CPAP delivery can have significantly different imposed resistances affecting airway pressure stability and work of breathing.

Aim

To compare CPAP performance of two resuscitation devices (Neopuff T-piece resuscitator and rPAP) in a neonatal lung model simulating spontaneous breathing effort at birth.

Methods

The parameters assessed were variation in delivered pressures (∆P), tidal volume (VT), inspiratory effort (model pressure respiratory muscle (PRM)) and work of breathing (WOB). Two data sequences were required with Neopuff and one with rPAP: (1) set PRM with changes in VT and (2) constant VT (preterm 6 mL, term 22 mL) with increased effort. Data were collected at CPAP settings of 5, 7 and 9 cmH2O using a 1 kg preterm (Compliance: 0.5 mL/cmH2O) and 3.5 kg term (1.0 mL/cmH2O) model.

Results

2298 breaths were analysed (760 rPAP, 795 Neopuff constant VT, 743 Neopuff constant PRM). With CPAP at 9 cmH2O and set VT the mean ∆P (cmH2O) rPAP vs Neopuff 1.1 vs 5.6 (preterm) and 1.9 vs 13.4 (term), WOB (mJ) 4.6 vs 6.1 (preterm) and 35.3 vs 44.5 (term), and with set PRM mean VT (ml) decreased to 6.2 vs 5.2 (preterm) and 22.3 vs 17.5 (term) p<0.001. Similar results were found at pressures of 5 and 7 cmH2O.

Conclusion

rPAP had smaller pressure swings than Neopuff at all CPAP levels and was thus more pressure stable. WOB was higher with Neopuff when VT was held constant. VT reduced with Neopuff when respiratory effort was constant.
Attack-Defending Contrastive Learning for Volumetric Medical Image Zero-Watermarking
Authors: Liu Xiyao , Yang Cundian , He Jianbiao , Fang Hui , Schaefer Gerald , Zhang Jian , Zhu Yuesheng , Zhang Shichao
Published: November 2024

Zero-watermarking is an emerging distortion-free copyright protection method for volumetric medical images. However, achieving both robustness against various malicious attacks and distinguishability between individual images remains challenging. In this article, we propose a novel attack-defending contrastive learning zero-watermarking (ADCL-ZW) scheme to tackle the above challenge using deep learning-based representations. In our approach, we design an attack-defending data enrichment mechanism to enhance the watermarking robustness by generating a large number of image samples under various watermarking attacks. Subsequently, features for both watermarking distinguishability and robustness are enhanced through application of a contrastive loss. In particular, we implement a dual-stream Siamese network architecture to effectively handle both signal attacks and geometric attacks in order to enhance the watermarking performance. Experimental results demonstrate that ADCL-ZW achieves stronger watermarking robustness and a better tradeoff between watermarking robustness and distinguishability compared with state-of-the art zero-watermarking methods. One of the highlighted metrics is that the false-negative rate of ADCL-ZW achieves 0.01 when a fixed false-positive rate is set to 1%, which is more than 13.3 times better than the benchmark methods.
When Automated Assessment Meets Automated Content Generation: Examining Text Quality in the Era of GPTs
Authors: Bevilacqua Marialena , Oketch Kezia , Qin Ruiyang , Stamey Will , Zhang Xinyuan , Gan Yi , Yang Kai , Abbasi Ahmed
Published: November 2024

The use of machine learning (ML) models to assess and score textual data has become increasingly pervasive in an array of contexts including natural language processing, information retrieval, search and recommendation, and credibility assessment of online content. A significant disruption at the intersection of ML and text are text-generating large-language models (LLMs) such as generative pre-trained transformers (GPTs). We empirically assess the differences in how ML-based scoring models trained on human content assess the quality of content generated by humans versus GPTs. To do so, we propose an analysis framework that encompasses essay scoring ML models, human- and ML-generated essays, and a statistical model that parsimoniously considers the impact of type of respondent, prompt genre, and the ML model used for assessment model. A rich testbed is utilized that encompasses 18,460 human-generated and GPT-based essays. Results of our benchmark analysis reveal that LLMs and transformer pretrained language models (PLMs) more accurately score human essay quality as compared to CNN/RNN and feature-based ML methods. Interestingly, we find that LLMs and transformer PLMs tend to score GPT-generated text 10–20% higher on average, relative to human-authored documents. Conversely, traditional deep learning and feature-based ML models score human text considerably higher. Further analysis reveals that even though the LLMs and transformer PLMs are exclusively fine-tuned on human text, they more prominently attend to certain tokens appearing only in GPT-generated text, possibly (in part) due to familiarity/overlap in pre-training. Our framework and results have implications for text classification settings where automated scoring of text is likely to be disrupted by generative AI.
When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We?
Authors: Chen Chong , Su Jianzhong , Chen Jiachi , Wang Yanlin , Bi Tingting , Yu Jianxing , Wang Yanli , Lin Xingwei , Chen Ting , Zheng Zibin
Published: November 2024

With the development of blockchain technology, smart contracts have become an important component of blockchain applications. Despite their crucial role, the development of smart contracts may introduce vulnerabilities and potentially lead to severe consequences, such as financial losses. Meanwhile, large language models, represented by ChatGPT, have gained great attentions, showcasing great capabilities in code analysis tasks. In this paper, we presented an empirical study to investigate the performance of ChatGPT in identifying smart contract vulnerabilities. Initially, we evaluated ChatGPT's effectiveness using a publicly available smart contract dataset. Our findings discover that while ChatGPT achieves a high recall rate, its precision in pinpointing smart contract vulnerabilities is limited. Furthermore, ChatGPT's performance varies when detecting different vulnerability types. We delved into the root causes for the false positives generated by ChatGPT, and categorized them into four groups. Second, by comparing ChatGPT with other state-of-the-art smart contract vulnerability detection tools, we found that ChatGPT's F-score is lower than others for 3 out of the 7 vulnerabilities. In the case of the remaining 4 vulnerabilities, ChatGPT exhibits a slight advantage over these tools. Finally, we analyzed the limitation of ChatGPT in smart contract vulnerability detection, revealing that the robustness of ChatGPT in this field needs to be improved from two aspects: its
uncertainty
in answering questions; and the
limited length
of the detected code. In general, our research provides insights into the strengths and weaknesses of employing large language models, specifically ChatGPT, for the detection of smart contract vulnerabilities.
ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets using LLMs
Authors: Kabir Azmain , Wang Shaowei , Tian Yuan , Chen Tse-Hsun (Peter) , Asaduzzaman Muhammad , Zhang Wenbin
Published: November 2024

Technical Q&A sites are valuable for software developers seeking knowledge, but the code snippets they provide are often uncompilable and incomplete due to unresolved types and missing libraries. This poses a challenge for users who wish to reuse or analyze these snippets. Existing methods either do not focus on creating compilable code or have low success rates. To address this, we propose ZS4C, a lightweight approach for zero-shot synthesis of compilable code from incomplete snippets using Large Language Models (LLMs). ZS4C operates in two stages: first, it uses an LLM, like GPT-3.5, to identify missing import statements in a snippet; second, it collaborates with a validator (e.g., compiler) to fix compilation errors caused by incorrect imports and syntax issues. We evaluated ZS4C on the StatType-SO benchmark and a new dataset, Python-SO, which includes 539 Python snippets from Stack Overflow across the 20 most popular Python libraries. ZS4C significantly outperforms existing methods, improving the compilation rate from 63% to 95.1% compared to the state-of-the-art SnR, marking a 50.1% improvement. On average, ZS4C can infer more accurate import statements (with an F1 score of 0.98) than SnR, with an improvement of 8.5% in the F1.
Repairs and Breaks Prediction for Deep Neural Networks
Authors: Ishimoto Yuta , Kondo Masanari , Ma Lei , Ubayashi Naoyasu , Kamei Yasutaka
Published: November 2024

With the increasing prevalence of software incorporating deep neural networks (DNNs), quality assurance for these software systems has become a crucial concern. To this end, various methods have been proposed to repair the misbehavior of DNNs by modifying their weights. However, these repair methods may not meet the developer's needs for a given dataset and model. In this study, we build prediction models for repair outcomes (i.e., repairs and breaks) to help determine whether the repair method is likely to work. By using our prediction models, developers and operators of DNNs can decide whether or not to apply a repair method, and if so, which method to use. Our prediction models utilize four metrics as explanatory metrics that represent the confidence or ambiguity in the DNN predictions. We experimented with four repair methods and 10 datasets. The experimental results demonstrate that our prediction models successfully select a repair method that meets developers’ needs in 16 out of 24 cases, resulting in an average time saving of 16.29% compared to the naive method. Based on these results, our prediction models can reduce costs for developers and operators when deciding whether to employ repair methods for real-world applications of DNNs.
Temporal-Incremental Learning for Android Malware Detection
Authors: Sun Tiezhu , Daoudi Nadia , Pian Weiguo , Kim Kisub , Allix Kevin , Bissyandé Tegawendé F. , Klein Jacques
Published: November 2024

Malware classification is a specific and refined task within the broader malware detection problem. Effective classification aids in understanding attack techniques and developing robust defenses, ensuring application security and timely mitigation of software vulnerabilities. The dynamic nature of malware demands adaptive classification techniques that can handle the continuous emergence of new families. Traditionally, this is done by retraining models on all historical samples, which requires significant resources in terms of time and storage. An alternative approach is Class-Incremental Learning (CIL), which focuses on progressively learning new classes (malware families) while preserving knowledge from previous training steps. However, CIL assumes that each class appears only once in training and is not revisited, an assumption that does not hold for malware families, which often persist across multiple time intervals. This leads to shifts in the data distribution for the same family over time, a challenge that is not addressed by traditional CIL methods. We formulate this problem as Temporal-Incremental Malware Learning (TIML), which adapts to these shifts and effectively classifies new variants. To support this, we organize the MalNet dataset, consisting of over a million entries of Android malware data collected over a decade, in chronological order. We first adapt state-of-the-art CIL approaches to meet TIML's requirements, serving as baseline methods. Then, we propose a novel multimodal TIML approach that leverages multiple malware modalities for improved performance. Extensive evaluations show that our TIML approaches outperform traditional CIL methods and demonstrate the feasibility of periodically updating malware classifiers at a low cost. This process is efficient and requires minimal storage and computational resources, with only a slight dip in performance compared to full retraining with historical data.
RGB-D Data Compression via Bi-Directional Cross-Modal Prior Transfer and Enhanced Entropy Modeling
Authors: Xu Yuyu , Zhang Pingping , Chen Minghui , Zhang Qiudan , Wu Wenhui , Zhang Yun , Wang Xu
Published: November 2024

RGB-D data, being homogeneous cross-modal data, demonstrates significant correlations among data elements. However, current research focuses only on a uni-directional pattern of cross-modal contextual information, neglecting the exploration of bi-directional relationships in the compression field. Thus, we propose a joint RGB-D compression scheme, which is combined with Bi-Directional Cross-Modal Prior Transfer (Bi-CPT) modules and a Bi-Directional Cross-Modal Enhanced Entropy (Bi-CEE) model. The Bi-CPT module is designed for compact representations of cross-modal features, effectively eliminating spatial and modality redundancies at different granularity levels. In contrast to the traditional entropy models, our proposed Bi-CEE model not only achieves spatial-channel contextual adaptation through partitioning RGB and depth features but also incorporates information from other modalities as prior to enhance the accuracy of probability estimation for latent variables. Furthermore, this model enables parallel multi-stage processing to accelerate coding. Experimental results demonstrate the superiority of our proposed framework over the current compression scheme, outperforming both rate-distortion performance and downstream tasks, including surface reconstruction and semantic segmentation. The source code will be available at
https://github.com/xyy7/Learning-based-RGB-D-Image-Compression
.
Diversity-Representativeness Replay and Knowledge Alignment for Lifelong Vehicle Re-identification
Authors: Cao Anqi , Wan Zhijing , Wang Xiao , Liu Wei , Wang Wei , Wang Zheng , Xu Xin
Published: November 2024

Lifelong Vehicle Re-Identification (LVReID) aims to match a target vehicle across multiple cameras, considering non-stationary and continuous data streams, which fits the needs of the practical application better than traditional vehicle re-identification. Nonetheless, this area has received relatively little attention. Recently, methods for Lifelong Person Re-Identification (LPReID) have been emerging, with replay-based methods achieving the best results by storing a small number of instances from previous tasks for retraining, thus effectively reducing catastrophic forgetting. However, these methods cannot be directly applied to LVReID because they fail to simultaneously consider the diversity and representativeness of replayed data, resulting in biases between the subset stored in the memory buffer and the original data. They randomly sample classes, which may not adequately represent the distribution of the original data. Additionally, these methods fail to consider the rich variation in instances of the same vehicle class due to factors such as vehicle orientation and lighting conditions. Therefore, preserving more informative classes and instances for replay helps maintain information from previous tasks and may mitigate the model's forgetting of old knowledge. In view of this, we propose a novel Diversity-Representativeness Dual-Stage Sampling Replay (DDSR) strategy for LVReID that constructs an effective memory buffer through two stages, i.e.
,
Cluster-Centric Class Selection and Diverse Instance Mining. Specifically, we first perform class-level sampling based on density in the clustered class-centered feature space and then further mine the diverse, high-quality instances within the selected classes. In addition, we introduce Maximum Mean Discrepancy loss to align the feature distribution between replay data and the new arrivals and apply L2 regularization in the parameter space to facilitate knowledge transfer, thus enhancing the model's generalization ability to new tasks. Extensive experiments demonstrate effective improvements of our method compared to current state-of-the-art lifelong ReID methods on the VeRi-776, VehicleID, and VERI-Wild datasets.
Variational Type Graph Autoencoder for Denoising on Event Recommendation
Authors: Zhang Shuo , Meng Xiangwu , Zhang Yujie
Published: November 2024

Recommendations for events play a pivotal role in facilitating the discovery of upcoming intriguing events within Event-Based Social Networks (EBSNs). Previous research has established the crucial significance of mining contextual features and implicit relationships to enhance recommendation performance and alleviate data sparsity issues. However, the noise inherent in contextual features exacerbates data sparsity and hampers the ability of previous methods to explore implicit relationships for mitigating data sparsity. To address this challenge, we propose a variational type graph autoencoder model that attenuates the influence of noise in different types of context features by introducing type-specific latent variables. First, we introduce a heterogeneous denoising convolution module composed of two components: (1) Denoising attention aggregation is proposed to mitigate the influence of noisy structures and uncover implicit relationships. (2) A heterogeneous normalization module leverages context features within the same type to alleviate the effects of noise in context features and data sparsity. Furthermore, we propose a learnable heterogeneous mixture prior that assists in assigning different priors to distinct types of latent variables, effectively modeling different types of contextual features. Through comprehensive experiments conducted on real-world datasets, we demonstrate the compelling performance of our model compared to state-of-the-art competitive approaches.
Sex-specific Associations between Left Ventricular Remodeling at MRI and Long-term Cardiovascular Risk
Authors: Weir-McCall Jonathan R. , Fitton Catherine A. , Gandy Stephen J. , Lambert Matthew , Littleford Roberta , Houston J. Graeme , Belch Jill J. F.
Published: November 2024

In a low- to intermediate-risk cohort, left ventricular remodeling at cardiac MRI predicted 10-year cardiovascular outcomes, with indexed left ventricular mass (LVM) and LVM-to-volume ratio being predictive in male and female participants, respectively.
Early subclinical stages of the inflammatory bowel diseases: insights from human and animal studies
Authors: Kelly Cecelia , Sartor R. Balfour , Rawls John F.
Published: November 2024

The inflammatory bowel diseases (IBD) occur in genetically susceptible individuals that mount inappropriate immune responses to their microbiota leading to chronic intestinal inflammation. The natural history of IBD progression begins with early subclinical stages of disease that occur before clinical diagnosis. Improved understanding of those early subclinical stages could lead to new or improved strategies for IBD diagnosis, prognostication, or prevention. Here, we review our current understanding of the early subclinical stages of IBD in humans including studies from first-degree relatives of patients with IBD and members of the general population who go on to develop IBD. We also discuss representative mouse models of IBD that can be used to investigate disease dynamics and host-microbiota relationships during these early stages. In particular, we underscore how mouse models of IBD that develop disease later in life with variable penetrance may present valuable opportunities to discern early subclinical mechanisms of disease before histological inflammation and other severe symptoms become apparent.
SUMO Regulation of Ion Channels in Health and Disease
Authors: Connolly Jenna G. , Plant Leigh D.
Published: November 2024

The small ubiquitin-like modifier (SUMO) protein pathway governs a panoply of vital biological processes including cell death, proliferation, differentiation, metabolism, and signal transduction by diversifying the functions, half-lives, and partnerships of target proteins in situ. More recently, SUMOylation has emerged as a key regulator of ion homeostasis and excitability across multiple tissues due to the regulation of a plethora of ion channels expressed in a range of tissue subtypes. Altogether, the balance of SUMOylation states among relevant ion channels can result in graded biophysical effects that tune excitability and contribute to a range of disease states including cardiac arrhythmia, epilepsy, pain transmission, and inflammation. Here, we consolidate these concepts by focusing on the role of ion channel SUMOylation in the central nervous system, peripheral nervous system, and cardiovascular system. In addition, we review what is known about the enigmatic factors that regulate the SUMO pathway and consider the emerging role of small molecule SUMO modulators as potential therapeutics in a range of diseases.
A Comparative Analysis of Primary and Bailout ADR in CTO‐PCI
Authors: Yang Lirui , Zhang Tao , Wang Gang , Ru Leisheng , Zhao Lin
Published: November 2024

Objective: To compare the efficiency and safety of primary and bailout antegrade dissection and re‐entry (ADR) during percutaneous coronary intervention (PCI) for chronic total occluded (CTO) lesions.

Methods: Patients who underwent ADR procedures for CTO lesions were enrolled in this study and were divided into two groups (primary ADR and bailout ADR) based on the initiation of ADR during PCI. The success rate and major adverse cardiovascular and cerebrovascular events (MACCE) during hospitalization were assessed as the primary endpoints. Procedure time, fluoroscopy time, wire crossing time, radiation dose, and contrast volume were considered as secondary endpoints.

Results: A total of 243 patients were enrolled in this study, with 127 patients receiving primary ADR and 116 receiving bailout ADR. No differences were found in baseline parameters between the two groups. The success rate was significantly higher in the primary ADR group compared to the bailout ADR group (89.0% versus 77.6%, respectively; p = 0.017). The incidence of in‐hospital MACCE was low in both groups, with no significant differences observed between them. Procedure time, radiation dose, and contrast volume were lower in the primary ADR group compared to the bailout ADR group. Cox regression analysis revealed that primary ADR and J‐CTO score ≥ 3 were independent predictors of technical success in CTO‐PCI.

Conclusions: Both primary and bailout ADR are safe strategies for CTO‐PCI. Primary ADR significantly improves the success rate of PCI for CTO compared to bailout ADR, with shorter operation time, lower radiation dose, and reduced contrast volume.
Effects of Dietary Taurine on Maturation Indices, Antioxidant Capacity, Ovaries Amino and Fatty Acids Profile, and Vitellogenin Gene Transcription Level in Penaeus vannamei Female Brooders
Authors: Mozanzadeh Mansour Torfi , Bahabadi Mahmoud Nafisi , Morshedi Vahid , Oujifard Amin , Agh Naser , Ghasemi Ahmad , Maneii Khalegh , Ebrahimi Hadi , Hamedi Shirin , Tamadoni Rezvan
Published: November 2024

A 30‐day research was carried out to examine the impacts of dietary taurine (Tau) on ovaries maturation and physiological responses of Penaeus vannamei female brooders (29.4 ± 0.2 g). A basal diet (497 g kg−1 protein and 140 g kg−1 lipid) was administered with graded levels of Tau ranging from 0 (control) to 2, 4, 6, 8, and 10 g kg−1. A total of 180 shrimp brooders were stocked into 18 250 L black circular polyethylene tanks. Female (n = 5) and male (n = 5) shrimps were stocked in each tank and supplied with seawater (35.2 ± 3.1 g L−1 salinity, 28.9 ± 1.4°C) and the experimental feeds were offered to shrimp twice a day at 5% of their biomass. Supplementing diet with 4–8 g Tau kg−1 reduced latency period after eye stalk ablation to spawning (5–6 days) that was associated with higher hepatopancreatic and gonadosomatic (except for 8 g Tau kg−1 diet) indices (p < 0.05). With 10 g Tau kg−1 diet hepatopancreas glutathione peroxidase activity and total antioxidant capacity increased and catalase activity increased by 6 g Tau kg−1 diet. Supplementing diet with Tau‐enhanced bile‐salt dependent lipase activity in the gut. Docosahexaenoic acid and Tau levels were elevated in the ovaries with the increment of dietary Tau level (p < 0.05). Plasma total protein, calcium, cholesterol, and high‐density lipoprotein increased with inclusion of 6–10 g Tau kg−1 diet. The transcription levels of vitellogenin, insulin-like growth factor II, superoxide dismutase, prophenoloxidase, and lysozyme genes transcription levels were upregulated in the hepatopancreas of shrimp brooders fed 6–10 g Tau kg−1 diet (p < 0.05). It seems that Tau at 4–8 g kg−1 diet by modulating lipid metabolism, antioxidant capacity, and immunocompetence can improve maturation and health status of P. vannamei brooders.
Manual Therapy Exerts Local Anti‐Inflammatory Effects Through Neutrophil Clearance
Authors: Liu Hongwen , Yuan Shiguo , Zheng Kai , Liu Gaofeng , Li Junhua , Ye Baofei , Wang Yangkun , Yin Li , Li Yikai
Published: November 2024

Background: Manual therapy (MT) has been widely used in China to treat local tissue inflammation for a long time. However, there is a lack of scientific evidence for using MT in anti‐inflammatory therapy, and its anti‐inflammatory mechanism needs further clarification.

Methods: We utilized MT to treat cardiotoxin (CTX) injury‐induced skeletal muscle inflammation in C57BL6/J mice. We analyzed the underlying mechanism by integrating single‐cell RNA sequencing (scRNA‐seq) with molecular techniques. Hematoxylin and eosin (H&E) and immunohistochemical (IHC) staining were used to assess skeletal muscle inflammation and muscle fiber cross‐sectional area (CSA). scRNA‐seq, immunofluorescence, and western blot were performed to determine cellular and molecular outcome changes.

Results: Compared with CTX injury‐induced skeletal muscle inflammatory mice, MT intervention significantly reduced proinflammatory cytokines interleukin (IL)‐1β, IL‐6, and tumor necrosis factor alpha (TNF‐α) expression levels; scRNA‐seq detected that neutrophil numbers and activity were maximum proportions increased in injured skeletal muscle among macrophage, T cells, B cells, endothelial cells, fast muscle cells, fibroblasts, and skeletal muscle satellite cells; and S100A9 gene expression was supreme in neutrophils. However, after treatment with MT, S100A9 protein expression and the numbers and activity of Ly6g+/Mpo+ neutrophils were significantly inhibited, thus reducing the inflammatory cytokine levels and exerting an anti‐inflammatory effect by early clearing neutrophils.

Conclusion: MT can mitigate localized inflammation induced by injured skeletal muscle, achieved by decreasing S100A9 protein expression and clearing neutrophils in mice, which may help advance therapeutic strategies for skeletal muscle localized inflammation.
A Arte da Direção no Teatro Tradicional Africano
Authors: Mark Tekena Gasper , Lodi Fabiano , Junqueira Liliana
Published: November 2024

The existence of the director in African traditional theatre has always been a subject of controversy amongst theatre scholars. While some scholars believe that the director exists in African traditional theatre, others, especially Euro-American theatre sympathizers, radically disagree. This belief is premised on the argument that African traditional performances do not have sufficient theatrical elements to qualify as theatre. However, this researcher supports the position that African theatre does exist, and tries to locate the place of the director in African traditional performances. Furthermore, it examines what constitutes African theatre, its advantages and disadvantages, and goes on to examine the directorial aesthetics and implications of directing on the African stage, as this would provide directors who want to direct or reinvent African traditional performances with the necessary information and guide they need. The study employs the case study and content analysis research approaches of the qualitative research method to realize set objectives. This researcher observed that studies on the art of directing in African traditional theatre are few, and therefore calls for more studies to be carried out in this area to fill the knowledge gap.
Atrial Topology for a Unified Understanding of Typical and Atypical Flutter
Authors: Duytschaever Mattias , Van den Abeele Robin , Carlier Niels , Bezerra Arthur Santos , Verstraeten Bjorn , Lootens Sebastiaan , Desplenter Karel , Okenov Arstanbek , Nezlobinsky Timur , Shah Dipen , Haas Annika , Luik Armin , Martens Jordi , El Haddad Milad , De Smet Maarten , De Becker Benjamin , Francois Clara , Le Polain de Waroux Jean-Benoit , Tavernier Rene , Knecht Sebastien , Hendrickx Sander , Vandersickel Nele
Published: November 2024

BACKGROUND:

Macroreentry stands as the predominant mechanism of typical and atypical flutter. Despite advances in mapping, many aspects of macroreentrant atrial tachycardia remain unsolved. In this translational study, we applied principles of topology to understand the activation patterns, entrainment characteristics, and ablation responses in a large clinical macroreentrant atrial tachycardia database.

METHODS:

Because the atrium can be topologically seen as a closed sphere with holes, we used a computational fixed spherical mesh model with a finite number of holes to induce and analyze macroreentrant atrial tachycardia. The ensuing insights were used to interpret high-density activation maps, postpacing interval-tachycardia cycle length values (difference between postpacing interval and tachycardia cycle length), and ablation response in 131 cases of typical and atypical flutter (n=106 left atrium, n=25 right atrium).

RESULTS:

Modeling of macroreentrant atrial tachycardia revealed that reentry on closed surfaces consistently manifests itself as paired rotation and that an odd number of critical boundaries is mathematically impossible. Together with mathematical confirmation by the index theorem, this led to a unifying construct that could explain the number of loops, difference between postpacing interval and tachycardia cycle length values, and ablation outcomes (termination, no change, or prolongation in tachycardia cycle length) in all 131 cases.

CONCLUSIONS:

Combining topology with the index theorem offers a novel and cohesive framework for understanding and managing typical and atypical flutter.
Gut Hormones in Heart Failure
Authors: Deis Tania , Goetze Jens P. , Kistorp Caroline , Gustafsson Finn
Published: November 2024

Heart failure (HF) is a syndrome affecting all organ systems. While some organ interactions have been studied intensively in HF (such as the cardiorenal interaction), the endocrine gut has to some degree been overlooked. However, there is growing evidence of direct cardiac effects of several hormones secreted from the gastrointestinal tract. For instance, GLP-1 (glucagon-like peptide-1), an incretin hormone secreted from the distal intestine following food intake, has notable effects on the heart, impacting heart rate and contractility. GLP-1 may even possess cardioprotective abilities, such as inhibition of myocardial ischemia and cardiac remodeling. While other gut hormones have been less studied, there is evidence suggesting cardiostimulatory properties of several hormones. Moreover, it has been reported that patients with HF have altered bioavailability of numerous gastrointestinal hormones, which may have prognostic implications. This might indicate an important role of gut hormones in cardiac physiology and pathology, which may be of particular importance in the failing heart. We present an overview of the current knowledge on gut hormones in HF, focusing on HF with reduced ejection fraction, and discuss how these hormones may be regulators of cardiac function and central hemodynamics. Potential therapeutic perspectives are discussed, and knowledge gaps are highlighted herein.
Virtual Reality for Preprocedure Planning of Covered Stent Correction of Superior Sinus Venosus Atrial Septal Defects
Authors: Stephenson Natasha , Rosenthal Eric , Jones Matthew , Deng Shujie , Wheeler Gavin , Pushparajah Kuberan , Schnabel Julia A. , Simpson John M.
Published: November 2024

BACKGROUND:

Covered stent correction (CSC) of a superior sinus venosus atrial septal defect is an alternative to surgery in selected patients, but anatomic variation means that assessment for CSC requires a 3-dimensional anatomic understanding. Heart VR is a virtual reality (VR) system that rapidly displays and renders multimodality imaging without prior image segmentation. The aim of this study was to evaluate the performance of the Heart VR system to assess patient suitability for CSC.

METHODS:

In a blinded fashion, 2 interventionalists reviewed preprocedural computed tomography scans using Heart VR to assess the feasibility of CSC, including the potential need for pulmonary vein protection. The total review time using VR was recorded.

RESULTS:

Using conventional imaging, 15 patients were deemed suitable for CSC, but at catheterization, 3 cases were unsuitable. Using VR, when both interventionalists agreed that a case was suitable for CSC (n=12), all proved technically feasible. In the 3 cases that were unsuitable for CSC, the interventionalists using VR were either uncertain (n=1) or did not agree on suitability (n=2). The strategy for pulmonary vein protection was correctly identified by interventionalist 1 and 2 in 9/12 and 8/12 cases, respectively. In cases where pulmonary vein protection was required intraprocedurally (n=5), this was correctly identified using Heart VR. Using VR, in 3 cases it was determined that pulmonary vein protection would be required, but this was not the case on balloon interrogation. VR data loading and review times were 82 seconds and 7 minutes, respectively. Verbal feedback indicated that Heart VR assisted in the assessment of case suitability.

CONCLUSIONS:

Heart VR is a rapid and effective tool for predicting suitability for CSC in patients with a superior sinus venosus atrial septal defect and could be a feasible alternative to segmented virtual or physical 3-dimensional models.
Movement Strategy Moderates the Effect of Spatially Congruent Cues on the Stability of Rhythmic Bimanual Finger Movements
Authors: Denyer Ronan , Boyd Lara A.
Published: November 2024

Spatially congruent cues increase the speed of bimanual reach decisions compared with abstract symbolic cues, particularly for asymmetric reaches. Asymmetric rhythmic bimanual movements are less stable than symmetric rhythmic movements, but it is not well understood if spatially congruent cues similarly increase the stability of asymmetric rhythmic bimanual movements. To address this question, in Experiment 1, participants performed symmetric and asymmetric bimanual rhythmic finger tapping movements at different movement frequencies in time with flickering spatially congruent and abstract symbolic stimuli. As expected, symmetric movements were more stable. Spatially congruent cues similarly increased the stability of symmetric and asymmetric movements compared with abstract symbolic cues. The benefits of spatial congruence and movement symmetry were restricted to high movement frequencies (>2 Hz). To better understand if the emergence of these effects at high movement frequencies was driven by a change in movement strategy, in Experiment 2, video of the hands was concurrently recorded during task performance. Markerless motion tracking software revealed that participants switched from discontinuous to continuous movement strategies with increasing movement frequency. Because discontinuous and continuous movements are thought to be controlled by distinct neurocognitive systems, this might explain why the beneficial effects of spatial congruence and response symmetry emerged only at high movement frequencies. Overall, results from the current study indicate that the perceptual quality of the stimulus use to cue movement frequency can have powerful effects on the stability of rhythmic bimanual movements, but that these effects may depend on whether discontinuous or continuous movement strategies are selected.