bluuebunny/crossref_metadata_2025_split huggingface dataset:
DCAF1 interacts with PARD3 to promote hepatocellular carcinoma progression and metastasis by activating the Akt signaling pathway
Authors: Zhang Jinyao , Shi Yuze , Ding Ke , Yu Weiwei , He Jianbo , Sun Beicheng 
Published: May 2024

Abstract
Background
Hepatocellular carcinoma (HCC) is a fatal malignancy with poor prognosis due to lack of effective clinical interference. DCAF1 plays a vital role in regulating cell growth and proliferation, and is involved in the progression of various malignancies. However, the function of DCAF1 in HCC development and the underlying mechanism are still unknown. This study aimed to explore the effect of DCAF1 in HCC and the corresponding molecular mechanism.

Methods
Quantitative real-time PCR, Western blot and immunostaining were used to determine DCAF1 expression in tumor tissues and cell lines. Subsequently, in vitro and in vivo experiments were conducted to explore the function of DCAF1 in tumor growth and metastasis in HCC. Coimmunoprecipitation, mass spectrometry and RNA sequencing were performed to identify the underlying molecular mechanisms.

Results
In this study, we found that DCAF1 was observably upregulated and associated with poor prognosis in HCC. Knockdown of DCAF1 inhibited tumor proliferation and metastasis and promoted tumor apoptosis, whereas overexpressing DCAF1 yielded opposite effects. Mechanistically, DCAF1 could activate the Akt signaling pathway by binding to PARD3 and enhancing its expression. We also found that the combined application of DCAF1 knockdown and Akt inhibitor could significantly suppress subcutaneous xenograft tumor growth.

Conclusions
Our study illustrates that DCAF1 plays a crucial role in HCC development and the DCAF1/PARD3/Akt axis presents a potentially effective therapeutic strategy for HCC.

Graphical Abstract
Deficiency of histone deacetylases 3 in macrophage alleviates monosodium urate crystals-induced gouty inflammation in mice
Authors: Yang Qi-Bin , Zhang Meng-Yun , Yang Liu , Wang Jie , Mi Qing-Sheng , Zhou Jing-Guo 
Published: May 2024

Abstract
Background
Gout is caused by monosodium urate (MSU) crystals deposition to trigger immune response. A recent study suggested that inhibition of Class I Histone deacetylases (HDACs) can significantly reduce MSU crystals-induced inflammation. However, which one of HDACs members in response to MSU crystals was still unknown. Here, we investigated the roles of HDAC3 in MSU crystals-induced gouty inflammation.

Methods
Macrophage specific HDAC3 knockout (KO) mice were used to investigate inflammatory profiles of gout in mouse models in vivo, including ankle arthritis, foot pad arthritis and subcutaneous air pouch model. In the in vitro experiments, bone marrow-derived macrophages (BMDMs) from mice were treated with MSU crystals to assess cytokines, potential target gene and protein.

Results
Deficiency of HDAC3 in macrophage not only reduced MSU-induced foot pad and ankle joint swelling but also decreased neutrophils trafficking and IL-1β release in air pouch models. In addition, the levels of inflammatory genes related to TLR2/4/NF-κB/IL-6/STAT3 signaling pathway were significantly decreased in BMDMs from HDAC3 KO mice after MSU treatment. Moreover, RGFP966, selective inhibitor of HDAC3, inhibited IL-6 and TNF-α production in BMDMs treated with MSU crystals. Besides, HDAC3 deficiency shifted gene expression from pro-inflammatory macrophage (M1) to anti-inflammatory macrophage (M2) in BMDMs after MSU challenge.

Conclusions
Deficiency of HDAC3 in macrophage alleviates MSU crystals-induced gouty inflammation through inhibition of TLR2/4 driven IL-6/STAT3 signaling pathway, suggesting that HDAC3 could contribute to a potential therapeutic target of gout.
Continuous lipreading based on acoustic temporal alignments
Authors: Gimeno-Gómez David , Martínez-Hinarejos Carlos-D. 
Published: May 2024

AbstractVisual speech recognition (VSR) is a challenging task that has received increasing interest during the last few decades. Current state of the art employs powerful end-to-end architectures based on deep learning which depend on large amounts of data and high computational resources for their estimation. We address the task of VSR for data scarcity scenarios with limited computational resources by using traditional approaches based on hidden Markov models. We present a novel learning strategy that employs information obtained from previous acoustic temporal alignments to improve the visual system performance. Furthermore, we studied multiple visual speech representations and how image resolution or frame rate affect its performance. All these experiments were conducted on the limited data VLRF corpus, a database which offers an audio-visual support to address continuous speech recognition in Spanish. The results show that our approach significantly outperforms the best results achieved on the task to date.
Demographic and economic inequality of antenatal care coverage in 4 African countries with a high maternal mortality rate
Authors: Belay Winini , Belay Amanuel , Mengesha Tariku , Habtemichael Mizan 
Published: May 2024

Abstract
Background
Maternal deaths are concentrated in low and middle-income countries, and Africa accounts for over 50% of the deaths. Women from socioeconomically disadvantaged households have higher morbidity and mortality rates and lower access to maternal health services. Understanding and addressing these inequalities is crucial for achieving the Sustainable Development Goals and improving maternal health outcomes. This study examines the demographic and economic disparities in the utilization of antenatal care (ANC) in four countries with high maternal mortality rates in Africa, namely Nigeria, Chad, Liberia, and Sierra Leone.

Method
The study utilised data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) from Nigeria, Chad, Liberia, and Sierra Leone. The data was obtained from the Health Equity Assessment Toolkit (HEAT) database. The study examined ANC service utilisation inequality in four dimensions such as economic status, education, place of residence, and subnational region across different subgroups by using four summary measures (Difference (D), Absolute Concentration Index (ACI), Population Attributable Risk (PAR), and Population Attributable Factor (PAF)).

Result
A varying level of inequality in ANC coverage across multiple survey years was observed in Nigeria, Chad, Liberia, and Sierra Leone. Different regions and countries exhibit varying levels of inequality. Disparities were prominent based on educational attainment and place of residence. Higher level of inequality was generally observed among individuals with higher education and those residing in urban areas. Inequality in ANC coverage was also observed by economic status, subnational region, and other factors in Nigeria, Chad, Liberia, and Sierra Leone. ANC coverage is generally higher among the richest quintile subgroup, indicating inequality. Nigeria and Chad show the highest levels of inequality in ANC coverage across multiple measures. Sierra Leone displays some variation with higher coverage among the poorest quintile subgroup.

Conclusion and recommendation
Inequalities in ANC coverage exist across age groups and survey years in Nigeria, Chad, Liberia, and Sierra Leone. Disparities are prominent based on education, residence, and economic status. Efforts should focus on improving access for vulnerable groups, enhancing education and awareness, strengthening healthcare infrastructure, and addressing economic disparities.
Worlds apart? Investigating acceptance and usage demands of carbon-based cosmetics and clothing across European countries
Authors: Wilkowska Wiktoria , Haverkämper Imke Tabea , Ziefle Martina 
Published: May 2024

Abstract
Background
Global warming and the increasing risk of natural disasters force us all to act. As the reduction of carbon dioxide (CO2) emissions has been proven effective but insufficient on its own, Carbon Capture and Utilization (CCU) technologies emerged to fill the gap. Using CCU technologies, CO2 is captured and further processed into valuable products instead of being emitted into the atmosphere.

Method
This study investigates the prevailing public perception of such CCU-based products by the example of clothing and cosmetics. We applied the method of conjoint measurement to experimentally examine context-related factors (= attributes) in different usage settings and explored the consumers’ decision profiles for or against the usage of CCU-based products (cosmetics and clothing). Conjoint measurements were realized as an online experiment, addressing acceptance patterns and preferences in four European countries (Germany, Norway, Spain, and Poland). In addition, we assessed general attitudes and affective assessments of the CCU products. A total of N = 828 participants took part in the study, and the international subsamples were comparable.

Results
Results revealed that health compatibility is the main adoption-driving factor in the decisions for or against the use of the products. Still, attributes like the environmental impact, product quality, and information flow play an important role as well, even though to a lesser extent. Participants from different countries significantly differ in their cognitive and affective evaluations of acceptance-related attributes.

Conclusions
The outcome provides insights into differences in Pan-European comparison and helps to understand the public motives and country-specific terms of use for CCU-based products, effectively establishing recommendations for policy and governance.
A study of spatial cognition in the rural heritage based on VR 3D eye-tracking experiments
Authors: Zhang Han , Andrade Bruno , Wang Xiaoqiong , Aburabee Ibrahim , Yuan Sinan 
Published: May 2024

Abstract
Traditional Chinese villages act as the essential carriers of China’s rural heritage. Such villages are considered to retain living practices of intangible heritage through know-how, artistic and folk customs, as well as a well-preserved architectural appearance. However, their conservation is at stake due to degradation, abandonment, and urbanization. Spatial cognition is one way of bringing people to the matter of what is important to conserve (attributes) and why they are important (values). This is done by analysing how people perceive and value rural heritage. Traditional methods of gathering spatial cognition data, such as laborious fieldwork or subjective qualitative analyses, often fall short of providing a holistic representation of real-world experiences. This article presents an innovative method for analysing cognitive features in traditional village spaces using an immersive virtual reality equipped with an eye-tracking system. We selected Cheng and Jitou, two traditional Chinese villages, as our case studies. In two virtual reality environments, we captured accurate 3D cognitive data, including participants’ locomotion, gaze point, and sightline. The results indicate that the accessibility of village roads affects the distribution of people’s locomotion, which in turn affects the distribution of people’s areas of interest; the changes in the rhythm of the sightline scale reflect the rhythm of spatial changes in the villages. By broadening the understanding of spatial cognition in traditional Chinese villages related to people’s values, this paper sheds light on an alternative approach to assess the cultural significance of such villages for higher conservation and sustainability.
Assessing the current landscape of AI and sustainability literature: identifying key trends, addressing gaps and challenges
Authors: Tripathi Shailesh , Bachmann Nadine , Brunner Manuel , Rizk Ziad , Jodlbauer Herbert 
Published: May 2024

AbstractThe United Nations’ 17 Sustainable Development Goals stress the importance of global and local efforts to address inequalities and implement sustainability. Addressing complex, interconnected sustainability challenges requires a systematic, interdisciplinary approach, where technology, AI, and data-driven methods offer potential solutions for optimizing resources, integrating different aspects of sustainability, and informed decision-making. Sustainability research surrounds various local, regional, and global challenges, emphasizing the need to identify emerging areas and gaps where AI and data-driven models play a crucial role. The study performs a comprehensive literature survey and scientometric and semantic analyses, categorizes data-driven methods for sustainability problems, and discusses the sustainable use of AI and big data. The outcomes of the analyses highlight the importance of collaborative and inclusive research that bridges regional differences, the interconnection of AI, technology, and sustainability topics, and the major research themes related to sustainability. It further emphasizes the significance of developing hybrid approaches combining AI, data-driven techniques, and expert knowledge for multi-level, multi-dimensional decision-making. Furthermore, the study recognizes the necessity of addressing ethical concerns and ensuring the sustainable use of AI and big data in sustainability research.
RETRACTED ARTICLE: Microwave-ultrasonic
assisted extraction of lignin to synthesize new nano micellar organometallic surfactants
for refining oily wastewater
Authors: Alhalafi M. H. , Rizk S. A. , Al-Malki E. S. , Algohary A. M. 
Published: May 2024

AbstractIn this work, a beneficial approach for efficient depolymerization of
lignin and controllable product distribution is provided. Lignin, an abundant aromatic
biopolymer, has the potential to produce various biofuels and chemical adsorption agents
and is expected to benefit the future circular economy. Microwave-ultrasonic (MW/US)
assisted efficient depolymerization of lignin affords some aromatic materials used in
manufacturing the starting material to be investigated. Some nano organometallic
surfactants (NOMS) based on Ni2+,
Cu2+, Co2+,
Fe3+, and Mn2+ besides
2-hydroxynaphth-sulphanilamide are synthesized to enhance oil recovery (EOR). In this
work, the assessment of the NOMS’s efficiency was improving the heavy oil recovery via
the study of the dynamic interfacial tension (IFT), contact angle, and chemical flooding
scenarios. The NOMS-Ni2+ exhibited the maximum reduction of
viscosity and yield values. Dropping the viscosity to 819.9, 659.89, and 499.9 Pa s from
blank crude oil viscosity of 9978.8, 8005.6, and 5008.6 Pa s respectively at
temperatures of 40, 60, and 80 °C was investigated. The reduction of
τB values was obtained also by
OMS-Ni2+. The minimum IFT was recorded against the
Ni2+ derivatives (0.1 × 10–1 mN
m−1). The complete wettability alteration was achieved
with the NOMS-Ni2+ surfactant (ɵ $$\cong 6.01).$$

≅
6.01
)
.

The flooding test has been steered in 3 sets using the sand-packed
model as a porous media at surfactant concentrations (1, 1.5, 2 and 2.5%) at 50 °C and
499 psi as injection pressure. The best value (ORs) formed for
NOMS-Ni2+ were 62, 81, 85.2, and 89% respectively as
compared with other NOMS-M2+ at the same concentrations. The
mechanism of alternating wettability was described in the text. The rheology of the used
heavy crude oil was investigated under temperatures of 40, 60, and 80 °C.
Graphical Abstract
Prognostic potentials of AI in ophthalmology: systemic disease forecasting via retinal imaging
Authors: Tan Yong Yu , Kang Hyun Goo , Lee Chan Joo , Kim Sung Soo , Park Sungha , Thakur Sahil , Da Soh Zhi , Cho Yunnie , Peng Qingsheng , Lee Kwanghyun , Tham Yih-Chung , Rim Tyler Hyungtaek , Cheng Ching-yu 
Published: May 2024

Abstract
Background
Artificial intelligence (AI) that utilizes deep learning (DL) has potential for systemic disease prediction using retinal imaging. The retina’s unique features enable non-invasive visualization of the central nervous system and microvascular circulation, aiding early detection and personalized treatment plans for personalized care. This review explores the value of retinal assessment, AI-based retinal biomarkers, and the importance of longitudinal prediction models in personalized care.

Main text
This narrative review extensively surveys the literature for relevant studies in PubMed and Google Scholar, investigating the application of AI-based retina biomarkers in predicting systemic diseases using retinal fundus photography. The study settings, sample sizes, utilized AI models and corresponding results were extracted and analysed.
This review highlights the substantial potential of AI-based retinal biomarkers in predicting neurodegenerative, cardiovascular, and chronic kidney diseases. Notably, DL algorithms have demonstrated effectiveness in identifying retinal image features associated with cognitive decline, dementia, Parkinson’s disease, and cardiovascular risk factors. Furthermore, longitudinal prediction models leveraging retinal images have shown potential in continuous disease risk assessment and early detection. AI-based retinal biomarkers are non-invasive, accurate, and efficient for disease forecasting and personalized care.

Conclusion
AI-based retinal imaging hold promise in transforming primary care and systemic disease management. Together, the retina’s unique features and the power of AI enable early detection, risk stratification, and help revolutionizing disease management plans. However, to fully realize the potential of AI in this domain, further research and validation in real-world settings are essential.
Association between systemic lupus erythematosus and osteoporosis: a mendelian randomization analysis
Authors: Xu Danfeng , Wu Bing 
Published: May 2024

Abstract
Background
Systemic Lupus Erythematosus (SLE) and Osteoporosis are two prevalent medical conditions. Previous studies have suggested a possible correlation between SLE and osteoporosis, though the underpinning causal relationship remains largely unknown. The current study aimed to elucidate the causal association between SLE and osteoporosis by employing a Mendelian randomization (MR) approach.

Methods
We performed two-sample MR analysis using the inverse variance-weighted (IVW), weighted median, and MR-Egger methods on publicly available summary statistics datasets using a SLE genome-wide association study (GWAS) as an exposure and osteoporosis GWASs in people with East Asia ancestry as outcomes. The pleiotropy and heterogeneity were examined using a variety of techniques, including the MR-Egger intercept, the MR-PRESSO approach, and the Cochran’s Q test.

Results
We selected 26 single-nucleotide polymorphisms from a SLE GWAS as instrumental variables for osteoporosis. The IVW (p < 0.05) method results support a potential association between SLE and osteoporosis. MR-Egger intercept (p = 0.82) and MR-PRESSO global test (p = 0.80) did not suggest evidence of horizontal or directional pleiotropy. Cochran’s Q test (p = 0.78) showed that there was no heterogeneity between IVs.

Conclusion
The results of MR analysis indicated that SLE is likely associated with an increased risk of osteoporosis incidence. Our findings highlight the need for increased awareness the potential risk of osteoporosis among SLE patients.
Physical activity moderates the association between school start time and sleep duration in a cross-sectional national sample of adolescents
Authors: Farley Zachary S. , Ward Mandilyn , Giuliani Nicole R. , Budd Elizabeth L. 
Published: May 2024

Abstract
Background
Adolescent insufficient sleep is an endemic issue that may result in compromised functioning throughout the course of the day and is associated with increased risk for a variety of adverse outcomes. Early school start time (SST) has been consistently found to be detrimental to adolescents’ sleep achievement on school nights. However, there are logistical barriers to changing SST. Evidence supports daily engagement in moderate-to-vigorous intensity physical activity (MVPA) to enhance adolescents’ nightly sleep achievement. However, the role of MVPA in the association between SST and sleep duration is unknown. This study examines the potential moderating effect of MVPA in the association between SST and sleep duration on a typical school day among adolescents.

Methods
This study examined data (collected in April and October 2014) from a national sample of 1132 adolescents (mage = 14.5 years) living in the United States from the Family Life, Activity, Sun, Health, and Eating study, a cross-sectional, internet-based survey. First, three linear regressions were computed to examine bivariate associations between SST, MVPA, and sleep duration while controlling for participant sex, race and ethnicity, household income, school level, and the presence of a TV in the bedroom. Next, a three-step multiple regression was computed with sleep duration as the dependent variable, and the final step included an interaction term between SST and MVPA.

Results
Later SST (b1 = 0.41, p < 0.001) and increased MVPA (b1 = 0.39, p < 0.001) were both associated with increased sleep duration, while SST and MVPA were not significantly associated. In the final multiple regression model, which included the interaction term, school day MVPA moderated the positive association between SST and school night sleep duration (b1 = − 3.7, p < 0.05), such that the greater the MVPA on a typical school day, the weaker the positive association between early SST and sleep duration. In post-hoc analysis, the interaction effect was only significant for females and not males.

Conclusions
The significant buffering effect of MVPA on the association between SST and sleep duration suggests that in the absence of SST changes, promoting MVPA among adolescents may be a promising strategy to mitigate insufficient sleep among US adolescents.
Assisted death for prisoners and forensic patients: complexity and controversy illustrated by four recent cases
Authors: Jones Roland M. , Simpson Alexander I. F. 
Published: May 2024

SummaryMedical assistance in dying (MAiD) (which includes euthanasia and assisted suicide) is available in an increasing number of countries. In Belgium, The Netherlands and Switzerland (and was due to be implemented in Canada from 2024) eligibility includes mental suffering in the absence of any physical disorder. There are particular ethical and legal issues when considering MAiD for those involuntarily detained in prisons and hospitals. We describe four recent cases that illustrate these complexities, and highlight issues of equivalence of healthcare and self-determination against concerns about the criteria for determining eligibility of those with non-terminal conditions as well as the objections raised by victims and families and the demands for justice.