bluuebunny/crossref_metadata_2025_split huggingface dataset:
Augmented Blood-Tumor Barrier Permeability and Enhanced Doxorubicin Delivery in Rat Brain Tumor Models Through Additional Focused Ultrasound Stimulation
Authors: Choi Hyo Jin , Han Mun , Jung Byeongjin , Huh Hyungkyu , Lee Eun-hee , Choi Jong-ryul , Park Juyoung 
Published: November 2024

Abstract

Focused ultrasound (FUS) has emerged as a promising technique for temporarily disrupting the blood-brain barrier (BBB) and blood-tumor barrier (BTB) to enhance the delivery of therapeutic agents. Despite its potential, optimizing FUS to maximize drug delivery while minimizing adverse effects remains a significant challenge. In this study, we evaluated a novel FUS protocol that incorporates additional FUS stimulation without microbubbles (MBs) ("FUS protocol") prior to conventional BBB disruption with MBs ("BBBD protocol") in a rat brain tumor model (n = 35). This approach aimed to validate its effectiveness in enhancing BBB/BTB disruption and facilitating doxorubicin delivery. T1-weighted contrast-enhanced and dynamic contrast-enhanced (DCE) MRI demonstrated significant increases in signal intensity and permeability (Ktrans) in the tumor region under the "FUS + BBBD protocol”, with 2.65-fold and 2.08-fold increases, respectively, compared to the non-sonicated contralateral region. These values were also elevated compared to the conventional "BBBD protocol" by 1.45-fold and 1.25-fold, respectively. Furthermore, doxorubicin delivery in the targeted region increased by 1.91-fold under the "FUS + BBBD protocol”, compared to a 1.44-fold increase using the conventional "BBBD protocol”. This novel FUS approach offers a promising, cost-effective strategy for enhancing drug delivery to brain tumors. While further studies are required to assess its applicability with different chemotherapeutics and tumor types, it holds significant potential for improving brain tumor treatment in both preclinical and clinical settings.
Divide-and-conquer strategy with engineered “ossification center” organoids for rapid bone healing via recruiting developmental cell community
Authors: Ouyang Hongwei , Zhang Xianzhu , Jiang Wei , Wu Xinyu , Xie Chang , Zhang Yi , Gu Yuqing , Hu Zihao , Li Liying , Liang Renjie , Zhang Tao , Sun Wei , Ye Jinchun , Wei Wei , Wang Xiaozhao , Hong Yi , Zhang Shufang , Cai Youzhi , Zou Xiaohui , Hu Yihe 
Published: November 2024

Abstract

Current approaches for bone repair are often focused on local delivery of growth factors that are aimed at coupled angiogenesis and osteogenesis. However, delayed revascularization and regeneration of severe bone defects are still challenging. In this study, we engineered an ossification center-like organoid (OCO) that consist of inner-core bone morphogenetic and neurotrophic spheroid generated via MSCs-loaded 3D printing, alongside the interstitially distributed outer-shell proangiogenic neurotrophic phase. Our results demonstrate that collective implantation of OCOs achieved rapid bone bridging with successive OC-like bone ossicles formation across the bone defect in a “divide-and-conquer” way. Single-cell RNA sequencing analysis unveiled a developmentally mimicking stem cell community that dominated with Krt8+ skeletal stem cells (SSCs) was uniquely recruited by the pro-regenerative in-situ organoid fusion and maturation. Particularly noteworthy is the specific expansion of Krt8+ SSCs concomitant with the simultaneous reduction of Has1+ migratory fibroblasts (MFs) 2 weeks post-OCO implantation. Furthermore, cross-species comparisons employing machine learning revealed high resemblance of relative Krt8+ SSCs/Has1+ MFs composition in bone regeneration with that in public data from developmental bone tissues. Our findings advocate an approach akin to “divide-and-conquer” utilizing engineered OC-like organoids for prompt regeneration of large-sized bone defects.
Fake news Detection on online Social Media
Authors: Deshmukh Ashwini , Govilkar Sharvari 
Published: November 2024

Abstract

In today's digital age, social media platforms are key for information sharing, but they also facilitate the rapid spread of fake news, especially during events like the COVID-19 pandemic. A system has been developed to address this issue by categorizing news articles into six categories, from "true" to "pants on fire." Data is gathered from diverse sources like Facebook, Twitter, YouTube, and trusted organizations such as WHO and UNICEF. Techniques like Principal Component Analysis (PCA) and machine learning algorithms, including Bi-LSTM neural networks with attention mechanisms, help improve detection accuracy. Despite challenges with multi-class datasets, the system achieved 51% accuracy and a 44.9% F-score. The system also assesses the credibility of news sources and authors by evaluating social media activity and potential biases. Further improvements are sought to refine performance and expand across social media platforms.
ATP6V1C1 and COPA: Autophagy-Related Markers for Tracking Progression from AKI to CKD—A Multi-Omics Investigation
Authors: Wang Yaojun , Li Qiang 
Published: November 2024

Abstract

This study explored the relationship between acute kidney injury (AKI) and chronic kidney disease (CKD), focusing on autophagy-related genes and their immune infiltration during the transition from AKI to CKD. We performed weighted correlation network analysis (WGCNA) using two microarray datasets (GSE139061 and GSE66494) in the GEO database, and identified autophagy signatures by KEGG, GO, and GSEA enrichment analysis. Machine learning algorithms such as LASSO, random forest and XGBoost were used to construct the diagnostic model, and the diagnostic performance of GSE30718 (AKI) and GSE37171 (CKD) was used as validation cohorts to evaluate its diagnostic performance. The study identified 14 autophagy candidate genes, among which ATP6V1C1 and COPA were identified as key biomarkers that were able to effectively distinguish between AKI and CKD. Immune cell infiltration and GSEA analysis revealed immune dysregulation in AKI, and these genes were associated with inflammation and immune pathways. Single-cell analysis showed that ATP6V1C1 and COPA were specifically expressed in AKI and CKD, which may be related to renal fibrosis. In addition, drug prediction and molecular docking analysis proposed SZ(+)-(S)-202-791 and PDE4 inhibitor 16 as potential therapeutic agents. In summary, this study provides new insights into the relationship between AKI and CKD and lays a foundation for the development of new treatment strategies.
Is Botulinum Toxin-A the Breakthrough in Premature Ejaculation Treatment? Insights from a Meta-Analysis of Randomised Controlled Trials
Authors: Mubarak Mohamed , Isa Qasim , Modgil Vaibhav , Pearce Ian 
Published: November 2024

Abstract

The ejaculatory reflex consists of emission and expulsion, with the latter involving rhythmic muscular contractions that propel seminal fluid. Botulinum toxin, through its inhibitory effects, has been hypothesized to improve premature ejaculation (PE). This study evaluates high-quality evidence on botulinum toxin-A injections into the bulbospongiosal muscle as a treatment for PE. We conducted a systematic review and meta-analysis of randomised-controlled trials following PRISMA guidelines. Outcomes included intravaginal ejaculatory latency time (IELT), Premature Ejaculation Profile (PEP) scores, and complications. Data were analysed using Microsoft Excel and R. ROB-2, Eggers test, and GRADE assessed risk of bias, publication bias, and certainty of evidence. Three randomised controlled trials were eligible, and covered data from 228 patients with 1:1 randomisation into intervention and control arms (100 units of BOTOX in 10mLs versus 10mLs of 0.9% NaCl). IELT & PEP scores demonstrated improvements at 1, 3, and 6 months, however, statistically significant was not achieved. Post-procedural complications were higher in the BOTOX group; however, all adverse effects were self-resolving. Given our findings, current high-quality evidence does not support using Botulinum Toxin-A in the management of premature ejaculation. Larger scale & standardised RCTs are recommended to conclusively outline its clinical benefits.
Platelet-specific TGFβ deficiency aggravates atherosclerosis, vascular inflammation and hypercholesterolemia in mice
Authors: Tan Shuai , Sun Yang , Sheng Zi , Min Yanan , Gisterå Anton , Zhang Junhao , Ketelhuth Daniel F.J. , Liao Wangjun , Andersson John , Hu Hu , Wang Miao , Hou Ming , Zhang Mingxiang , Peng Jun , Ma Chunhong , Li Nailin 
Published: November 2024

Abstract

Background
Atherosclerosis involves inflammatory and thrombotic mechanisms, to which platelets, CD4+ T effector cells, and transforming growth factor β (TGFβ) all contribute importantly. Platelets are the principal source of circulating TGFβ, which profoundly regulates CD4+ T effector cell responses. The impact of platelet-derived TGFβ on atherosclerosis is, however, unknown.
Objectives
The present work investigated how platelet-specific TGFβ-deficiency impacts CD4+ T effector cell responses and atherogenesis.
Methods
Murine platelet-selective TGFβ-deficiency (plt-TGFβ−/−) was created by a Pf4-Cre approach, and an atherosclerotic mouse model was established by functional abrogation of Ldlr and 10–15 weeks of a high-fat diet in plt-TGFβ−/− mice and their non-plt-TGFβ−/− littermates.
Results
En face Oil Red O staining of the aorta showed more atherosclerotic lesion formation in plt-TGFβ−/− mice, with significant increases in both lesion size and lesion coverage of the total aortic area. Cryosections of the aortic root confirmed the aggravation of atherogenesis. Platelet-derived TGFβ deficiency increased circulating platelets and plasma levels of total cholesterol, LDL-cholesterol, and triglycerides after a 10 or 15 week high-fat diet period. RNA sequencing and proteomic analyses of the aorta showed signs of CD4+ T effector cell and macrophage activation in plt-TGFβ−/− mice.
Conclusions
Platelet-specific TGFβ deficiency aggravates atherosclerosis, via increasing arterial inflammation and plasma levels of cholesterol. Our findings demonstrate that platelet-derived TGFβ is prominently athero-protective.
Combating Deepfakes: An Entropy-Aware Framework for Detecting Forged Visual and Textual Information
Authors: Wu Hongchen , Jing Zhaorong , Fang Xiaochang , Li Hongxuan , Li Meng , Yu Hongzhu , Yu Bing , Zhang Huaxiang 
Published: November 2024

Abstract

The rise of deepfakes and users' susceptibility to online manipulation underscore the critical need for effective detection methods in scholarly research. Detecting multimodal deepfakes—particularly in inflammatory posts—poses unique challenges, as these combine multiple media types to increase believability and emotional impact. To address this, we propose the DEFUTE framework, an entropy-based method that assesses feature consistency across images and text through four modules: deepfake detection, image similarity, text similarity, and text-image matching. Using the DamCNN algorithm, DEFUTE identifies facial forgeries, while image and text similarity modules analyze key visual and semantic features. The text-image matching module verifies alignment between descriptions and images to spot discrepancies. DEFUTE demonstrates high accuracy in identifying deepfake content, with future efforts focused on enhancing generalization and integrating multimodal data for even greater precision.
Words from the Wards: Paronyms in Medical Article Titles
Authors: Lysanets Yuliia , Bieliaieva Olena , Uvarkina Olena , Skrypnikova Taisa , Kiryk Tamara , Khmil Tetiana , Hutsol Mariia 
Published: November 2024

Abstract

This paper explores the use of paronyms in article titles sourced from the PubMed database. The study identified 43 paronymic pairs, 6 paronymic triads, and 1 paronymic tetrad across 207 medical article titles. We analyzed the detected paronymic lexemes in terms of their etymology, morphology, orthography, phonology, stylistic features, and pragmatic functions. In medical article titles, paronyms underlie paronomasia (puns), alliteration, antithesis, rhetorical questions, metaphor, repetition, and rhyme. These rhetorical devices ensure the compelling and memorable effect of article titles that not only capture readers’ attention but also convey the complexity and highlight the relevance of the papers’ content. Other pragmatic functions of paronyms in article titles include establishing tone, inducing curiosity, creating ambiguity, and encouraging exploration. By examining how paronyms are used in article titles, EAP students and early career writers can develop a deeper understanding of the subtle distinctions between paronymic lexemes and subsequently use them correctly, recognize the rhetorical devices and employ the pragmatic strategies in academic writing, thus enhancing their language proficiency and developing critical thinking skills. This will ultimately promote mastery of the skills needed to create engaging and compelling titles, which can increase the visibility and impact of research articles.
Strong Nonreciprocity in a Bistable Pendulum with Contactless Coupling to a Monostable Pendulum
Authors: Rouleau Michael , Booker Zachary , Shi Chengzhi , Meaud Julien 
Published: November 2024

Abstract

This article studies the nonreciprocity of a system that consists of a bistable element coupled to a monostable element through a contactless magnetic interaction. To illustrate the concept, the bistable element is physically realized using a pendulum that interacts with a stationary magnet and the monostable element is a classical pendulum. A numerical model is implemented to simulate the nonlinear dynamics of the system. Both simulations and experiments show that the system exhibits a strong amplitude-dependent nonreciprocity in response to initial excitations. At small input amplitudes, the system has an intrawell response with minimal transmission of energy whether the excitation is exerted on the side of the bistable pendulum or on the other side. However, at high input amplitude, a strong nonreciprocal behavior is observed: excitation of the bistable pendulum causes an interwell response which considerably reduces the distance between the two pendulums and allows energy to be efficiently transmitted through the contactless magnetic interaction; excitation of the monostable pendulum does not cause any interwell response and results in limited energy transmission. The combination of bistability and contactless nonlinear interactions allows the system to exhibit very strong amplitude-dependent nonreciprocity, which may be useful in a wide range of applications.
Global Stability Ensured Controller Design for Nonlinear Markov Jump Systems Based on Contraction Theory
Authors: Xv Wenxin , Wan Haiying , Luan Xiaoli , Liu Fei 
Published: November 2024

Abstract

This paper presents a novel state feedback controller design method based on contraction theory for continuous-time nonlinear Markov jump systems (NMJSs) to achieve the global stability. The developed approach employs the concept of virtual displacement to transform the global stability problem in Riemannian space into a piece wise local analysis. To address the limitations of traditional Lyapunov methods that rely on the initial values of system states and information at equilibrium points, a Lyapunov-like function is constructed in the tangent space of the system’s state space. The constructed function evolves dynamically with variations in both time and state. This allows for stability analysis that does not depend on initial conditions or equilibrium information. As a result, the global stability of NMJSs is guaranteed. Furthermore, a state feedback control methodology is developed to make the designed controller effective on a global scale. The effectiveness and superiority of the proposed method are illustrated through both a numerical example and an application to aircraft.
Establishment of a depression model using dexamethasone-treated three-dimensional cultured rat cortical cells
Authors: Seo Mi Kyoung , Jeong Sehoon , Cheon Woo Seok , Lee Dong Yun , Lee Sumin , Lee Gyu-Hui , Kang Deok-Gyeong , Seog Dae-Hyun , Kim Seong-Ho , Lee Jung Goo , Park Sung Woo 
Published: November 2024

Abstract

In vitro models are useful for exploring the molecular mechanisms underlying impaired neuroplasticity in depression. In this study, we developed a three-dimensional spheroid model using the synthetic glucocorticoid dexamethasone to investigate its effects on key pathways involved in neuroplasticity, specifically focusing on BDNF, sirtuin 1, and mTORC1 signaling. A micro-spheroid device was fabricated using photolithography and soft lithography, and cortical spheroids were generated from primary rat cortical cells. These spheroids were treated with varying concentrations of dexamethasone, and their structure included neurons, astrocytes, microglia, and oligodendrocytes. Dexamethasone treatment (100, 200, and 300 µM) resulted in a dose-dependent reduction in cell viability, BDNF mRNA expression, and neurite outgrowth. At 100 µM, dexamethasone reduced the expression of BDNF and sirtuin 1 and decreased phosphorylation of ERK1/2. It also lowered the phosphorylation levels of mTORC1, 4E-BP1, and p70S6K, as well as synaptic proteins such as PSD-95 and GluA1. Dexamethasone treatment inhibited pathways related to neuroplasticity. While the dexamethasone-treated spheroids may serve as a basis for developing an in vitro model of depression, further validation is required to confirm its broader applicability.
A Review of challenges and solution in the detection of disease in the Brinjal leaves
Authors: Abisha S. , Stephen S. Frank 
Published: November 2024

Abstract

Crop damage and monetary losses occur due to plant diseases. At specified periods, farmers closely monitor their crops in the field to look for infections or diseases. In place of manual diagnosis, computers have been used to provide computerized tracking and recognition of a variety of diseases.This study makes a contribution to denoising algorithms that improve contrast, edge details and picture details. To isolate the leaf affected area, segmentation was carried out. Image fusion is performed using the segmented image obtained from several segmentation techniques, and features are extracted according to structural, texture, and color criteria. Furthermore, an image fusion technique based on Discrete Shearlet Transforms (DST) is applied to improve imaging quality while reducing redundancy. The color, texture, and structural elements of the fused images are retrieved and fed into the Artificial Neural Network (ANN) for classification, resulting in improved performance. When compared to other classification methods (SVM, MSVM, FFNN, and RFNN), the accuracy required for the DST-based fusion approach and the Radial Basis Function Neural Network is relatively high. The classification accuracy was 99.35%, with 89.24% sensitivity, 94.67% specificity, and 90.12% precision.
Evaluation of permafrost environmental sustainability based on the game theory and cloud matter-element extension method
Authors: Ye Yi-Ning , Chou Ya-Ling , Cao Wei , Xu Jia-Wei , Wang Ai-Jun 
Published: November 2024

Abstract

Aiming at the uncertainties and the randomness and fuzziness of classification grade boundary in the existing evaluation of permafrost environmental sustainability, a comprehensive model based on game theory and cloud matter-element extension model (CMEEM) was proposed. Based on game theory, the combination weights of each indicator were obtained by integrating the decision making trial and evaluation laboratory (DEMATEL) method and entropy weight method. Thus, the combination of subjective and objective weights was realized. Using the advantages of uncertainty inference and qualitative and quantitative analysis of the cloud matter-element extension model, a comprehensive evaluation vector was obtained by calculating the membership degree between the subject element and the hierarchical cloud. Then, the evaluation grade was determined according to the principle of maximum membership degree. Taking the case area along the Chaida’er-Muli Railway as an example, the expected value Ex was 3.811, and the grade is IV, indicating that the permafrost level was good, but the phenomenon of permafrost degradation has begun to appear in this region. The case study showed that the evaluation results of the model are objective and accurate, consistent with the actual situation and other research. This comprehensive model can provide a new method for the evaluation of permafrost environment sustainability and obtain more information.
Unequal Emissions, Unequal Impacts: How High-Income Groups Disproportionately Contribute to Climate Extremes Worldwide
Authors: Schoengart Sarah , Nicholls Zebedee , Hoffmann Roman , Pelz Setu , Schleussner Carl-Friedrich 
Published: November 2024

Abstract

One of the fundamental injustices of climate change is that those least responsible often bear the brunt of its impacts.
This injustice persists not only between countries but also on the individual level within societies. Here, we assess
how greenhouse gas emissions from consumption and investments attributable to the wealthiest population groups
from 1990 to 2019 have influenced present-day (2020) global mean temperature levels as well as monthly temperature
and potential drought extremes. We combine emission inequality data with an emulator-based modelling framework,
enabling a systematic attribution of changes in regional extremes worldwide. We find that the top 10% wealthiest
individuals globally contributed about 6.5 times the global average to global warming (0.40°C ± 0.16°C), the top 1%
even 20 times the average (0.12°C ± 0.05°C). These disproportionate contributions further amplify for extreme events,
with the top 10% contributing about 7 times more to the emergence of 1-in-100 year heat and potential drought events
than the global average (11.5 ± 3.9 and 4.7 ± 2.8 additional occurrences), the top 1% 25 times more (4.0 ± 1.3
and 1.7 ± 0.9 additional occurrences). Emissions from the the wealthiest 10% in the United States and China, the
two largest greenhouse gas emitters, are associated with a two- to three-fold increase in the frequency of heat and
drought extremes across vulnerable regions. Quantifying the relationship between wealth disparities and climate
change impacts can assist the discourse on climate equity and justice.
Dual-Channel Branch Mechanism-basedVisual Defect Detection
Authors: Xu Jianbing , Zhou Jiangxin , Xu Dongxu , Chen Yu 
Published: November 2024

Abstract

Recently, defect detection has received widespread attention in the fields of graphic images and multimedia vision. Although existing visual detection methods have achieved promising performance, they are mainly targeted at object detection tasks under ideal conditions (sufficient lighting, clean background, etc.). When faced with complex and harsh conditions in reality (such as excessive line of sight and noisy background), the performance drops sharply. To address the potential hazards posed by abnormal interferences in power transmission lines due to natural environmental factors and human activities (such as bird nests, bird damage, foreign object coverage, and construction work), this paper proposes a defect detection algorithm for distribution lines based on a dual-branch mechanism. The proposed method first effectively locates and extracts the features of distribution line defects (bird nests, bird damage, foreign object coverage, and construction work). It then integrates a Feature Pyramid Network (FPN) to achieve multi-scale feature fusion, enhancing the prominence of defect areas to improve the accuracy and robustness of the model in target detection tasks. Finally, utilizing the dual-branch mechanism facilitates multi-task learning for both classification and regression training of defects. Experimental results demonstrate that our proposed method outperforms the widely adopted standard architecture deep models in terms of effectiveness, better meeting the practical requirements of industrial inspections and the visual applications for graphic images. Source code can be found at: https://github.com/jxsiaj/DCBM.git.