bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating Adaptive Video Streaming over Multipath QUIC with Shared Bottleneck Detection
Authors: Kimura Bruno , Ferlin Simone , Paiva Thomas , Mahmoodi Toktam , Brunstrom Anna , Alay Ozgu 
Published: January 2025

The promises of multipath transport are to aggregate bandwidth, improve resource utilization, and enhance reliability. In this paper, we demonstrate that the way multipath coupled congestion control is defined today leads to a suboptimal resource utilisation when network paths are disjoint, i.e., they do not share a bottleneck link. With growing interest in standardising Multipath QUIC (MPQUIC), we have implemented the practical shared bottleneck detection (SBD) algorithm from
RFC8382
in MPQUIC (MPQUIC-SBD). Through extensive experiments, we evaluate MPQUIC-SBD in the context of video streaming with various Adaptive Bitrate (ABR) algorithms, addressing both ABR classes of rule-based and learning-based solutions. We demonstrate that MPQUIC-SBD accurately detects shared bottlenecks over 90% of the time, depending on the ABR algorithm, as the size of the video segments increases. In non-shared bottleneck scenarios, when MPQUIC-SBD detects that its QUIC subflows do not share the same network resources, it decouples their congestion windows accordingly, enabling video throughput gains of up to 37% compared to MPQUIC. These gains translate directly into improved video quality metrics, including higher bitrate, better resolution, and reduced buffering, resulting in an enhanced quality of experience for users.
Monkeypox Virus Outbreak 2022: Assessment of Knowledge Among Healthcare Workers in Two Countries—India and Saudi Arabia
Authors: Naik Sachin , Vellappally Sajith , Al Kheraif Abdulaziz Abdullah , Alsarani Majed M. , Basavarajappa Santhosh , Alhassoun Raghad Khalid , Hashem Mohamed , Fouad Hassan , Saleem Murtaza , M Asiri Faisal Ali , Mohammed Awaiyer Meshal Saeed 
Published: January 2025

Background: Healthcare workers play a crucial role in limiting the spread of the monkeypox virus. Studies show that healthcare worker’s (HCWs) understanding and communication about preventing infectious diseases can inspire various groups of individuals.Objective: This study aimed to compare the knowledge of HCWs in India and Saudi Arabia regarding monkeypox virus infection.Methods: A cross‐sectional survey was conducted among HCWs in India and Saudi Arabia. The questionnaire was developed using information from the World Health Organization and Centers for Disease Control and Prevention websites. The validation of the questionnaire (Cronbach’s alpha = 0.87) was conducted for data collection. The mean scores between different demographic groups were compared using Student’s t‐test and one‐way ANOVA.Results: A total of 848 participants responded to the questionnaire (India = 424 and Saudi Arabia = 424). The average knowledge score in India was 12.59 ± 2.49, and in Saudi Arabia, it was 13.25 ± 2.99 out of 20. The percentage of participants with good knowledge about monkeypox was 22.2% in India and 36.1% in Saudi Arabia. Participants with poor knowledge about monkeypox constituted 11% in India and 12% in Saudi Arabia.Conclusion: HCWs in both countries had moderate to poor knowledge about the monkeypox outbreak. This might be because monkeypox is not prevalent in these countries. More education is needed to improve HCWs knowledge about monkeypox infection.
Evaluating the Antidiabetic Activity of Aloe niebuhriana Latex in Alloxan‐Induced Diabetic Rats and the Development of a Novel Effervescent Granule‐Based Delivery System
Authors: Moharram Bushra Abdulkarim , Alburyhi Mahmoud Mahyoob , Al-Maqtari Tareq , Faisal Abdu 
Published: January 2025

Background: Ethnomedicine exhibits potential in developing affordable effective antidiabetic agents.Aim: This work aimed to explore the antidiabetic properties of Aloe niebuhriana latex extract both in vivo, utilizing alloxan‐induced diabetic rats, and in vitro, through α‐amylase enzyme testing. Additionally, it sought to formulate optimal effervescent granules derived from the extract.Methods: The α‐amylase inhibition assay was performed using the α‐amylase kit using biochemical analyzers. Experimental diabetes was induced in animals with alloxan. On Day 14 postdiabetes induction, body weight, fasting blood glucose, and lipid profile parameters were determined. Also, six effervescent granule preparations of the extract were formulated using wet granulation. Based on its physical and organoleptic properties, a formulation was selected and optimized.Results: The extract displayed modest α‐amylase inhibition, with an IC50 value of 439.2 μg/mL. Both doses of A. niebuhriana extract (200 and 400 mg/kg) significantly reduced blood glucose level compared to their respective Day 1 levels (p < 0.001). Moreover, the extract at a dose of 400 mg/kg significantly normalized lipid profile compared to the diabetic control groups (p < 0.05 − 0.001). Six formulations containing the extract were prepared (F1–F6), and F6 containing 200 mg of the extract was selected for optimization due to its favorable odor, taste, foaming, and effervescent properties, high solubility, and absence of turbidity and adhesion. The formulated F6 granules successfully met the quality parameters assessed including flow time, pH effervescent time, angle of repose, bulk density, tapped density, Carr’s index, and Hausner’s ratio.Conclusion: This study highlights the antidiabetic potential of A. niebuhriana latex extract, potentially attributed to its hypolipidemic, hypoglycemic, and α‐amylase inhibitory effects. The successful formulation and evaluation of the extract as effervescent granules suggest its potential as an antidiabetic drug.
A Phase I Clinical Trial of Intrahepatic Artery Delivery of TG6002 in Combination with Oral 5-Fluorocytosine in Patients with Liver-Dominant Metastatic Colorectal Cancer
Authors: West Emma J. , Sadoun Alain , Bendjama Kaidre , Erbs Philippe , Smolenschi Cristina , Cassier Philippe A. , de Baere Thierry , Sainte-Croix Sophie , Brandely Maud , Melcher Alan A. , Ismail Fay , Scott Karen J. , Bennett Angela , Banks Emma , Gasior Ewa , Kent Sarah , Kurzawa Marta , Hammond Christopher , Patel Jai V. , Collinson Fiona J. , Twelves Chris , Anthoney D. Alan , Swinson Dan , Samson Adel 
Published: January 2025

Abstract

Purpose:
Effective treatment for patients with metastatic cancer is limited, particularly for those with colorectal cancer with metastatic liver lesions, in which accessibility to numerous tumors is essential for favorable clinical outcomes. Oncolytic viruses (OV) selectively replicate in cancer cells; however, direct targeting of inaccessible lesions is limited when using conventional intravenous or intratumoral administration routes.

Patients and Methods:
We conducted a multicenter, dose-escalation, phase I study of vaccinia virus, TG6002, via intrahepatic artery (IHA) delivery in combination with the oral prodrug 5-fluorocytosine to 15 patients with metastatic colorectal cancer.

Results:
Successful IHA delivery of replication-competent TG6002 was achieved, as demonstrated by the virus within tumor biopsies. Functional transcription of the FCU1 transgene indicates viral replication within the tumor, with higher plasma 5-fluorouracil associated with patients receiving the highest dose of TG6002. IHA delivery of TG6002 correlated with a robust systemic peripheral immune response to the virus with activation of peripheral blood mononuclear cells, associated with a proinflammatory cytokine response and release of calreticulin, potentially indicating immunogenic cell death. Gene Ontology analyses of differentially expressed genes reveal a significant immune response at the transcriptional level in response to treatment. Moreover, an increase in the number and frequency of T-cell receptor clones against both cancer antigens and neoantigens, with elevated functional activity, may be associated with improved anticancer activity. Despite these findings, no clinical efficacy was observed.

Conclusions:
In summary, these data demonstrate the delivery of OV to tumor via IHA administration, associated with viral replication and significant peripheral immune activation. Collectively, the data support the need for future studies using IHA administration of OVs.
Inhibition of DKK-1 by WAY262611 Inhibits Osteosarcoma Metastasis
Authors: Tal Adit , Gunawardana-Zeigler Shimara , Peng Da , Tan Yuqi , Munoz Perez Natalia , Offenbacher Rachel , Kastner Laurel , Ciero Paul , Randolph Matthew E. , Gong Yun , Deng Hong-Wen , Cahan Patrick , Loeb David M. 
Published: January 2025

Abstract
Osteosarcoma is the most common primary malignant bone tumor in childhood. Patients who present with metastatic disease at diagnosis or relapse have a very poor prognosis, and this has not changed over the past four decades. The Wnt signaling pathway plays a role in regulating osteogenesis and is implicated in osteosarcoma pathogenesis. DKK-1 inhibits the canonical Wnt signaling pathway, causing inhibition of osteoblast differentiation and disordered bone repair. Our lab previously demonstrated that an mAb against DKK-1 prevented metastatic disease in a mouse model. This study expands upon those findings by demonstrating similar results with a small-molecule inhibitor of DKK-1, WAY262611, both in vitro and in vivo. WAY262611 was evaluated in vitro on osteosarcoma cell lines, including proliferation, caspase activation, cell-cycle analysis, and signaling pathway activation. We utilized our orthotopic implantation/amputation model of osteosarcoma metastasis in vivo to determine the impact of WAY262611 on primary tumor progression and metastatic outgrowth of disseminated tumor cells. Differentiation status was determined using single-cell RNA sequencing. We show here that WAY262611 activates canonical Wnt signaling, enhances nuclear localization and transcriptional activity of β-catenin, and slows proliferation of osteosarcoma cell lines. We also show that WAY262611 induces osteoblastic differentiation of a patient-derived xenograft of osteosarcoma in vivo, as well as inhibiting metastasis. This work credentials DKK-1 as a therapeutic target in osteosarcoma, allowing for manipulation of the Wnt signaling pathway and providing preclinical justification for the development of new biologics for the prevention of osteosarcoma metastasis.
Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks
Authors: Zhu Zhichao , Qi Yang , Lu Wenlian , Wang Zhigang , Cao Lu , Feng Jianfeng 
Published: January 2025

Abstract
Spiking neural networks (SNNs) have attracted significant interest in the development of brain-inspired computing systems due to their energy efficiency and similarities to biological information processing. In contrast to continuous-valued artificial neural networks, which produce results in a single step, SNNs require multiple steps during inference to achieve a desired accuracy level, resulting in a burden in real-time response and energy efficiency. Inspired by the tradeoff between speed and accuracy in human and animal decision-making processes, which exhibit correlations among reaction times, task complexity, and decision confidence, an inquiry emerges regarding how an SNN model can benefit by implementing these attributes. Here, we introduce a theory of decision making in SNNs by untangling the interplay between signal and noise. Under this theory, we introduce a new learning objective that trains an SNN not only to make the correct decisions but also to shape its confidence. Numerical experiments demonstrate that SNNs trained in this way exhibit improved confidence expression, reduced trial-to-trial variability, and shorter latency to reach the desired accuracy. We then introduce a stopping policy that can stop inference in a way that further enhances the time efficiency of SNNs. The stopping time can serve as an indicator to whether a decision is correct, akin to the reaction time in animal behavior experiments. By integrating stochasticity into decision making, this study opens up new possibilities to explore the capabilities of SNNs and advance SNNs and their applications in complex decision-making scenarios where model performance is limited.
Replay as a Basis for Backpropagation Through Time in the Brain
Authors: Cheng Huzi , Brown Joshua W. 
Published: January 2025

Abstract
How episodic memories are formed in the brain is a continuing puzzle for the neuroscience community. The brain areas that are critical for episodic learning (e.g., the hippocampus) are characterized by recurrent connectivity and generate frequent offline replay events. The function of the replay events is a subject of active debate. Recurrent connectivity, computational simulations show, enables sequence learning when combined with a suitable learning algorithm such as backpropagation through time (BPTT). BPTT, however, is not biologically plausible. We describe here, for the first time, a biologically plausible variant of BPTT in a reversible recurrent neural network, R2N2, that critically leverages offline replay to support episodic learning. The model uses forward and backward offline replay to transfer information between two recurrent neural networks, a cache and a consolidator, that perform rapid one-shot learning and statistical learning, respectively. Unlike replay in standard BPTT, this architecture requires no artificial external memory store. This approach outperforms existing solutions like random feedback local online learning and reservoir network. It also accounts for the functional significance of hippocampal replay events. We demonstrate the R2N2 network properties using benchmark tests from computer science and simulate the rodent delayed alternation T-maze task.
Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm
Authors: Lenfesty Brendan , Bhattacharyya Saugat , Wong-Lin KongFatt 
Published: January 2025

Abstract
Decision formation in perceptual decision making involves sensory evidence accumulation instantiated by the temporal integration of an internal decision variable toward some decision criterion or threshold, as described by sequential sampling theoretical models. The decision variable can be represented in the form of experimentally observable neural activities. Hence, elucidating the appropriate theoretical model becomes crucial to understanding the mechanisms underlying perceptual decision formation. Existing computational methods are limited to either fitting of choice behavioral data or linear model estimation from neural activity data. In this work, we made use of sparse identification of nonlinear dynamics (SINDy), a data-driven approach, to elucidate the deterministic linear and nonlinear components of often-used stochastic decision models within reaction time task paradigms. Based on the simulated decision variable activities of the models and assuming the noise coefficient term is known beforehand, SINDy, enhanced with approaches using multiple trials, could readily estimate the deterministic terms in the dynamical equations, choice accuracy, and decision time of the models across a range of signal-to-noise ratio values. In particular, SINDy performed the best using the more memory-intensive multi-trial approach while trial-averaging of parameters performed more moderately. The single-trial approach, although expectedly not performing as well, may be useful for real-time modeling. Taken together, our work offers alternative approaches for SINDy to uncover the dynamics in perceptual decision making and, more generally, for first-passage time problems.
What Kinds of Computations Can Young Children Perform Over Non-Symbolic Representations of Small Quantities?
Authors: Cheng Chen , Kibbe Melissa M. 
Published: January 2025

Abstract
Children can manipulate non-symbolic representations of both small quantities of objects (about four or fewer, represented by the parallel individuation system) and large quantities of objects (represented by the analog magnitude system, or AMS). Previous work has shown that children can perform a variety of non-symbolic operations over AMS representations (like summing and solving for an unknown addend), but are not able to perform further operations on the derived solutions of such non-symbolic operations. However, while the computational capacity of AMS has been studied extensively in early childhood, less is known about the computational capacity of the parallel individuation system. In two experiments, we examined children’s ability to perform two types of arithmetic-like operations over representations of small, exact quantities, and whether they could subsequently perform novel operations on derived quantity representations. Four-6-year-old US children (n = 99) solved two types of non-symbolic arithmetic-like problems with small quantities: summation and unknown addend problems. We then tested whether children could use the solutions to these problems as inputs to new operations. Results showed that children more readily solved non-symbolic small, exact addition problems compared to unknown addend problems. However, when children did successfully solve either kind of problem, they were able to use those derived solutions to solve a novel non-symbolic small, exact problem. These results suggest that the parallel individuation system is computationally flexible, contrasting with previous work showing that the AMS is more computationally limited, and shed light on the computational capacities and limitations of representing and operating over representations of small quantities of individual objects.
Preschoolers Represent Abstract Relations Predicated on Kind Membership
Authors: Zhu Rebecca 
Published: January 2025

Abstract
Recent work demonstrates that U.S. preschoolers can represent the abstract relational concepts same and different when these abstract relational concepts are predicated upon perceptual dimensions (e.g., size, shape, color). The current research investigates whether preschoolers (n = 192; predominantly White, upper middle class, U.S. convenience sample) can also represent the abstract relational concepts same and different when these abstract relational concepts are predicated upon abstract dimensions (e.g., kind membership). Experiment 1 shows that, at baseline, 4-year-olds fail at a relational match-to-sample (rMTS) task with familiar kinds. However, Experiment 2 shows that 4- and 5-year-olds, but not 3-year-olds, succeed at a rMTS task with familiar kinds when provided with training involving noun labels. Experiment 3 shows that 4- and 5-year-olds also succeed at a rMTS task with novel kinds when provided with training involving noun labels but not adjective labels, suggesting that noun labels but not adjective labels cue children’s attention towards kind membership. Moreover, participants frequently provided explanations appealing to sameness and difference when justifying their responses. Taken together, these results suggest that, with training, preschoolers are capable of representing abstract relations predicated on abstract, as well as perceptual, dimensions.
Noninvasive prediction of coronary artery disease severity: Comparative analysis of electrocardiographic findings and risk factors with SYNTAX and Gensini score
Authors: Mirjalili Farzaneh-Sadat , Baghiani Tahere , Badkoubeh Faezeh , Andishmand Abbas , Sarebanhassanabadi Mohammadtaghi , Mohammadi Hamidreza , Salehi-Abargouei Amin , Motallaei Maryam , Seyedhosseini Seyed Mostafa 
Published: January 2025

Objective: Coronary artery disease (CAD) remains a significant global health burden, characterized by the narrowing or blockage of coronary arteries. Treatment decisions are often guided by angiography-based scoring systems, such as the Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) and Gensini scores, although these require invasive procedures. This study explores the potential of electrocardiography (ECG) as a noninvasive diagnostic tool for predicting CAD severity, alongside traditional risk factors. Methods: This retrospective cross-sectional study was conducted on 348 CAD patients who underwent coronary angiography. Demographic data, ECG findings, SYNTAX, and Gensini scores were collected. The association between ECG findings and demographic information with the severity of coronary artery stenosis, as assessed by SYNTAX and Gensini scores, was investigated using SPSS software, version 23. Results: Significant associations were observed between CAD severity and risk factors such as male gender, diabetes mellitus (DM), and smoking. Additionally, certain ECG indicators, including Q waves and ST depression (STD), showed significant correlations with CAD severity, particularly according to the Gensini score. Conclusion: This study underscores the utility of ECG and clinical factors in identifying severe CAD, offering cost-effective diagnostic alternatives to angiography. Integrating various parameters into a single score is crucial in clinical practice, providing a stronger diagnostic and prognostic tool without increasing costs. Further comprehensive studies are warranted to refine risk prediction models and improve CAD management strategies.
Validation of Pediatric Sequential Organ Failure Assessment (pSOFA) Scores to Predict Critical Events in the Pediatric Intensive Care Unit
Authors: Badke Colleen M. , Wang Austin , Daniels Latasha A. , Sanchez-Pinto L. Nelson 
Published: January 2025

Objective To determine the prognostic value of the Pediatric Sequential Organ Failure Assessment (pSOFA) to discriminate critical events, including code events and intubations, in the pediatric intensive care unit (PICU). Methods We performed an observational cohort study of all critical events in a quaternary care PICU between 5/2020 and 4/2023. Critical events were extracted from our hospital communications platform and from the electronic health record (EHR). The pediatric sequential organ failure assessment (pSOFA) scores were prospectively calculated in real-time in our EHR every 15 min during the study period for data-driven situational awareness and were retrospectively analyzed for this study. Each encounter was divided into 6-h time blocks and we assessed the performance of the highest pSOFA score in each block at discriminating the occurrence of a critical event in the subsequent block. Results There were 5687 unique patient encounters included in the analysis. Critical events were identified in 578 out of 169 486 time blocks (prevalence 0.3%), which included 103 code events and 498 intubation events, in 392 unique PICU encounters. The total pSOFA score in a 6-h time block was significantly associated with a subsequent code event (odds ratio [OR] 1.19, 95% CI 1.13-1.24) or intubation (OR 1.13, 95% CI 1.10-1.15). Several organ-specific pSOFA subscores were also significantly associated with the outcomes. Area under the receiver operating characteristic curve (AUROC) for the total pSOFA score was 0.67 for a code event and 0.65 for intubation. Using a pSOFA score cutoff of ≥8, the positive predictive value was 0.8% and the negative predictive value was 99.7% for any critical event. Conclusions The pSOFA score is significantly associated with critical events in the PICU, however, it does not have adequate performance to be used for situational awareness by itself.