bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nitrogen-containing bisphosphonate induces enhancement of OPG expression and inhibition of RANKL expression via inhibition of farnesyl pyrophosphate synthase to inhibit the osteogenic differentiation and calcification in vascular smooth muscle cells
Authors: Xu Wei , Gong Lifeng , Tang Weigang , Lu Guoyuan 
Published: February 2024

Abstract

Background
The osteogenic differentiation of vascular smooth muscle cells (VSMCs) plays a key role in the progression of Vascular calcification（VC）. The previous research showed that nitrogen-containing bisphosphonate（N-BP）had inhibitory effect on the osteogenic differentiation and calcification induced by high phosphorus in VSMCs. However, it is not clear how N-BP inhibits the osteogenic differentiation and calcification in VSMCs via specific regulatory mechanisms.
Methods
β-glycerophosphate (β-GP) was used to induce the osteogenic differentiation and calcification in VSMCs. In some experiments, VSMCs were cultured with β-GP , or β-GP plus different concentrations of N-BP. In some other experiments, the VSMCs were cultured with β-GP plus N-BP, β-GP plus N-BP and farnesol (FOH), or β-GP plus N-BP and geranylgeraniol (GGOH). Alizarin red S staining and determination of calcium content were used to detect calcium deposition.Western Blotting were used to detect expressions of proteins(OPG and RANKL ) and osteogenic marker proteins (Runx2 and OPN).
Results
β-GP induced the osteogenic differentiation and calcification in VSMCs , increased RANKL protein expression and had no significant effect on OPG protein expression. N-BP increased OPG protein expression and decreased RANKL protein expression in VSMCs of osteogenic differentiation and calcification induced by β-GP. In addition, N-BP reduced the osteogenic marker proteins (Runx2 and OPN) expression and calcium deposition in VSMCs of osteogenic differentiation and calcification induced by β-GP. These effects of N-BP on the osteogenic differentiation and calcification in VSMCs were concentration-dependent, which could be reversed by the downstream products of farnesyl pyrophosphate synthase(FPPS) in mevalonate pathway such as FOH or GGOH.
Conclusion
N-BP increases OPG expression and decreases RANKL expression via inhibition of FPPS to inhibit the osteogenic differentiation and calcification of VSMCs
A Comparison of Intraoperative Ultrasound and Post- Operative Mri in Paediatric Intra Axial Tumours
Authors: Fuad Nadiah Ahmad , Alias Azmi , Rosli Fadzlishah Johanabas , Idris Zamzuri , Ismail Rohazly , An Adi Afiq Md 
Published: February 2024

Abstract
Background Malignant tumours of the Central Nervous System (CNS) is the second most common paediatric malignancy, following haematological malignancy. CNS tumours depend significantly on the extent of tumour resection. In the past decade, intraoperative ultrasound (IOUS) has evolved into a widespread neuroimaging tool that offers real-time surgical guidance, and is a widely accessible imaging modality with minimal identified risk or additional operative time, and also lower economic investment. Recent studies found a strong correlation between IOUS and post operative MRI findings when evaluating extent of tumour resection in adult population suggesting that IOUS might have significant clinical implications, however not many studies involved the paediatrics population. The objective of our study was to compare correlation and reliability of the ultrasound as compared to MRI for tumour resection in paediatric population. We also evaluated IOUS as a real-time navigation tool during surgical resection of intra axial tumours in paediatric patients.
Methods This was a prospective observational study done in a Hospital Tunku Azizah, Kuala Lumpur. Patients aged less than 12 years old, admitted between 1st December 2019 to 30th November 2021 with preoperative MRI diagnosis of intra-axial brain tumour were recruited in this study. IOUS was performed intraoperatively, and post-operative MRI performed within 24-72 hours post-op. IOUS utility assessment scoring was performed intraoperatively.
Results We analysed a total of 25 paediatric patients that met the inclusion criteria. Concordance analysis between IOUS evaluation and MRI showed good agreement (kappa = 0.527). A multivariate logistic regression analysis was performed to look for any significant factors of discordance, and none of the variables were found significant for discordance. Hosmer and Lemeshow goodness of fit test was performed, and showed that our model is a good fit, with a good prediction value of 0.497.
Conclusion The use of IOUS allowed reliable intra operative imaging modality to achieve more successful gross total resection of brain tumours in paediatrics.
0.68% of solar-to-hydrogen efficiency and super-high photostability: Panel H2O-to-H2 conversion based on a novel organic-inorganic membrane catalyst
Authors: Li Wei , Duan Wen , Liao Guocheng , Gao Fanfan , Wang Yusen , Cui Rongxia , Zhao Jincai , Wang Chuanyi 
Published: February 2024

Abstract

Solar-driven flat-panel H2O-to-H2 (HTH) conversion is an important technology for value-added solar fuel production. However, most frequently used particulate photocatalysts are hard to achieve stable photocatalysis in flat-panel reaction module due to the influence of mechanical shear force by fluid and generated bubbles. Constructing stable photocatalytic membrane can effectively address the critical issues of particulate photocatalysts. Herein, a highly active CdS@SiO2-Pt composite with rapid CdS-to-Pt electron-transfer kinetics and restrained photoexciton recombination kinetics was prepared to process into an organic-inorganic membrane by compounding with organic ferroelectric polyvinylidene fluoride (PVDF). This organic-inorganic synergistically interface networked membrane catalyst displays super-high photostability and excellent operability, dramatically overcoming the drawback of inorganic particulate catalysts, and achieving remarkable simulated sunlight (SSL)-driven alkaline (pH = 14.0) HTH activity (213.48 mmol∙m-2∙h-1) with 0.68% of solar-to-hydrogen (STH) efficiency. No obvious variation in its appearance and micromorphology was observed even being recycled for 50-times, which considerably outperforms the existing membrane photocatalysts. Subsequently, a homemade panel reaction system was fabricated to achieve alkaline water-splitting to obtain a 0.05% of STH efficiency under SSL-irradiation. This study opens up a new prospect for practical application of panel photocatalytic hydrogen production with organic-inorganic interface networked membrane technology.
Causal relationships between systolic blood pressure and ischemic stroke based on two-sample Mendelian randomization
Authors: Liu Xiao-Hu , Yang Ze-Hua , Zhou Yue , Luo Jia-zhuang , Yao Run-lan 
Published: February 2024

Abstract

Context: Stroke is a major public health issue globally. Therefore, ongoing research on the risk factors for ischemic stroke (IS) is essential for its prevention.
Objective: To assess the potential causal relationship between systolic blood pressure (SBP) and ischemic stroke (IS).
Design and Setting: A total of 810,865 SBP and 440,328 IS samples from publicly-available genome-wide association studies (2020 and 2018, respectively) were analyzed. A two-sample Mendelian randomization (MR) study was conducted to assess the causal relationships between SBP and the risk of IS. Inverse-variance weighting (IVW), and weighted median (WME), weighted mode (WM), and MR-Egger regression methods were also undertaken. Odds ratios (OR) and 95% confidence intervals (95%CI) were calculated. Heterogeneity and the presence of horizontal multicollinearity were tested using a Cochran’s Q test and MR-Egger intercept, respectively.
Main Outcome Measures: Correlation between SBP and IS was the main study outcome. Results: IVW showed a positive correlation between genetically-predicted SBP and IS (OR = 1.849, 95%CI = 1.628–2.099, P = 2.844×10-21). MR-Egger (OR = 2.192, 95%CI = 1.626–2.257, P = 2.610×10-7), WME (OR = 1.945, 95%CI = 1.676–2.257, P = 7.752×10-18), and WM methods (R = 2.246, 95%CI = 1.666–3.030, P = 4.008×10-8) supported the existence of a causal relationship between SBP and IS. MR-Egger intercept testing did not detect horizontal pleiotropy. The “leave-one-out” sensitivity analysis showed no bias in the results.
Conclusions:There is a positive causal relationship between genetically-predicted SBP and IS, suggesting that elevated SBP is a risk factor for IS.
Smart Home AI Model (SHAM): Optimizing Switches and Sockets space in Residential Building during Planning/Construction through Multilayer Perceptron Estimation
Authors: Singh Ashish Singh Ashish , Saxena Shubham Saxena Shubham , Singh Shailendra Kumar Singh Shailendra Kumar , Pandey Aatrey Pandey Aatrey 
Published: February 2024

Abstract

This study presents the development and evaluation of a Multilayer Perceptron (MLP) model for estimating the optimal number of switches and sockets space in houses not designed by professional engineers. Utilizing data from 145 houses across diverse cities, the study employs the Back Propagation Levenberg-Marquardt (BPLM) technique for MLP model estimation The SHAM is AI based multilayer perceptron model which recommends optimum number of switches and sockets space by considering factors like topography, type of property, size of property, type of occupancy. This model predicts the most suitable combination of switches and sockets space for a newly planned house. Utilizing data from 145 houses across diverse cities, the MLP architecture selection was based on performance metrics such as Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) from testing and training data. The statistical analysis identified the 26-9-1 MLP architecture with a minimum MAPE value of 0.2572. Subsequently, this selected neural network model was applied to predict the optimal number of switches and sockets space. The study demonstrates the efficacy of the developed Smart Home AI Model (SHAM), proving valuable for both unprofessional and professional civil engineers during the planning stage. The implementation of the AI-based SHAM model is discussed, highlighting its adaptability to get optimum number of switches and sockets space without a detailed designing of electrical circuits. Results from real-world simulations demonstrate the effectiveness of the model in achieving energy savings, efficient construction and user satisfaction compared to traditional, non-optimized setups.
Drug-loaded MITO@HA nanodrugs for evaluating the efficacy of targeted therapy for pancreatic cancer
Authors: Liu Fengjun , Xu Zhiyang , Jia Xiaochao , Tang Yidan , Chen Mingsheng , Chen Chuan , Fang Fang , Shi Xiudong , Chen Tianyou , Shi Yuxin 
Published: February 2024

Abstract

The purpose of this study was to evaluate the efficiency of mitoxantrone hydrochloride (MITO@HA) as a targeted pancreatic cancer therapy. MITO@HA binds to sodium hyaluronate, which is highly expressed in pancreatic cancers. This study seeks to evaluate MITO@HA treatment efficacy, clarify its inhibitory effect on pancreatic cancer, and provide an experimental basis for the use of organic polymer nanoparticles loaded with antitumor drugs to treat pancreatic cancer. This treatment strategy was developed for pancreatic cancer based on the hydrophobic behavior of the nanopharmaceutical MITO@HA. The average particle size of MITO@HA was 51.4 ± 2.3 nm, and the particles had a spherical structure. CCK-8 assays revealed that both MITO and MITO@HA inhibited the proliferation of pancreatic cancer cells. that the most suitable experimental conditions were determined to be exposing pancreatic cancer cells to 0.5 uM/L MITO@HA for 2 days. PANC-1 pancreatic cancer cells and pancreatic cancer tissues were found to express high levels of CD44. In in vitro experiments, MITO@HA inhibited G0/G1 phase arrest, increased apoptosis, and decreased cell replication, cell migration and invasion in the pancreatic cancer cell cycle compared to MITO alone. Therefore, we believe that MITO@HA has a good tumor cell inhibitory effect. Furthermore, in vivo experiments revealed that the tumor volume in nude mice in the MITO@HA group decreased (P < 0.05), and both MITO and MITO@HA treatment decreased the tumor growth curves, with MITO@HA decreasing them more than MITO alone. Compared with those in the control group and the MITO group, the HE staining of tumors in the MITO@HA group showed massive liquefaction necrosis of the tumor tissues. Safety evaluation of the nude mice in the MITO@HA group revealed that the mice had a normal blood profile, normal liver and kidney function, and normal myocardial enzymes. The above results indicate that MITO@HA can effectively accumulate in pancreatic cancer tumor tissue through the EPR effect and CD44 receptor targeting, leading to liquefaction and necrosis of tumor tissue, thereby effectively reducing tumor growth. The above results showed that MITO@HA is highly safe and can enhance the antitumor effect on pancreatic cancer, providing an experimental basis for clinical application.
Deciphering and Constructing the Quorum Sensing Language “Interpreter” Ecosystem for Microbial Community
Authors: Wu Shengbo , Zhang Hong , Zhou Yongsheng , Xu Chengyang , Yuan Boxin , Wang Haijiao , Chen Danlei , Liu Chunjiang , Caiyin Qinggele , Wu Hao , Yang Aidong , Zhao Kun , Qiao Jianjun 
Published: February 2024

Abstract
Background
Microbes in diverse natural communities communicate via quorum sensing (QS) signals that act as microbial languages. However, earlier work on the investigation on microbial interactions and systematic stability mostly based on the diverse modelling-assistant ecological pairwise interactions (such as cooperation and competition) or metabolite-based interactions (such as division of labor and auxotrophies). The investigation and synthesis of multiple QS signals transmission in the QS communication network (QSCN) are less explored. The aim of this work is to decipher and construct another type of microbial interactions, i.e., QSCN, in the complex environment by considering cell heterogeneity, environmental interference and other factors, so as to provide the basis and guidance for the more practical applications of gut microbiota composed of different strains.
Results
In this study, to deepen the understanding of QS-based complex interactions, we firstly constructed and analyzed the directed QSCN including nine QS systems for a validated stable gut microbiome. Then, QS language “interpreter” was proposed and constructed in five Escherichia coli strains to simulate the linear and circular QSCN among natural microbial communities. Specifically, by combining single-cell microscopic and bulk-level macroscopic measurements, we investigate the performances and dynamics of synthetic three-strain QS language “interpreter” ecosystems that are in response to dramatic environmental changes. Data analysis and experimental results showed that the existence of complex QS language "interpreter" ecosystems promote the stability maintenance of microbial community. Furthermore, a comprehensive kinetic computational model was developed for the optimization of tunable directed QSCN. Finally, the perspectives of the QSCN for the effective control of microbial communities were discussed and summarized.
Conclusion
Microbial QS language “interpreter” is an interesting and broad conceptual advance for the construction of the large-scale microbial communities. The dynamic characteristics and transmission law of QS "interpreter" in microbial communication studied in this paper is an important basis for understanding microbial social communications. The findings in this study will help to optimize QS-based consortia and benefit their potential applications in ecosystem-based engineering and microbiome-based therapeutics.
Knockdown of PTEN Disrupts PINK1/Parkin-mediated Mitophagy and Promotes Hippocampal Neuronal Cell Death Following Experimental Status Epilepticus
Authors: Lin Li-Han , Hsu Chung-Yao , Huang Chin-Wei , Lin Tsu-Kung , Chen Shang-Der , Pan Hsiu-Yung , Chuang Yao-Chung 
Published: February 2024

Abstract
Aberrant mitophagy due to mitochondrial defects via oxidative stress has a strong potential to cause epilepsy. However, PINK1 signaling regarding damaged mitochondria- and oxidative stress-mediated mitophagy during status epilepticus (SE) remains to be fully elucidated. Therefore, the present study aimed to clarify this molecular mechanism in SE animal model. We used pilocarpine-induced SE animal model to investigate the molecular mechanism of SE. Our data exhibited that the hippocampal tissue of rats during SE increased the expression and PTEN and mitophagy-related markers (PINK1, Parkin, p-Drp1 and LC3B-II), showed the mitochondria dysfunction (oxygen consumption and mitochondrial fission), increased the oxidative stress, displayed an mitophage feature (mitophagic vacuole formation), and induced apoptotic cell death. Of note, SE-increased oxidative stress from the hippocampal tissue induced PINK1/Parkin-mediated mitophagy effects via an PTEN-dependent manner. Inhibition of PTEN expression by siRNA transfection in the hippocampal tissue blocked PINK1/Parkin-mediated mitophagy effect caused by oxidative stress. Subsequently, inhibition of PTEN expression enhanced Drp1-mediated mitochondria fission and ensuing damaged mitochondrial-induced apoptotic cell death. In conclusions, these findings reveal that hippocampal neuronal cells during SE display features of oxidative stress, damaged mitochondria, apoptotic cell death and mitophagy, and PTEN contribute to activate these program in hippocampal neuronal cells.
Noradrenergic signaling controls Alzheimer's disease pathology via activation of microglial β2 adrenergic receptors
Authors: Majewska Ania , Le Linh , Feidler Alexis , Li Herman , Kara-Pabani Kallam , Lamantia Cassandra , O'Banion  M. Kerry 
Published: February 2024

Abstract
Norepinephrine (NE) is a potent anti-inflammatory agent in the brain. In Alzheimer’s disease (AD), the loss of NE signaling heightens neuroinflammation and exacerbates amyloid pathology. NE inhibits surveillance activity of microglia, the brain’s resident immune cells, via their β2 adrenergic receptors (β2ARs). Here, we investigate the role of microglial β2AR signaling in AD pathology in the 5xFAD mouse model of AD. We found that loss of cortical NE projections preceded the degeneration of NE-producing neurons and that microglia in 5xFAD mice, especially those microglia that were associated with plaques, significantly downregulated β2AR gene expression early in amyloid pathology. Importantly, dampening microglial β2AR signaling worsened plaque load and the associated neuritic damage, while stimulating microglial β2AR signaling attenuated amyloid pathology. Our results suggest that microglial β2AR could be explored as a potential therapeutic target to modify AD pathology.
Assessment of Public Breast Cancer Awareness among Females in Klang Valley, Malaysia
Authors: Hee Mei Qi , Fatokun Omotayo Oladuntoye , Abdullah Norlia , Farukkh Muhammad Junaid 
Published: February 2024

Abstract

Background
Breast cancer has now replaced lung cancer as the most common form of cancer, and its burden has been rising over the past decades, including in Malaysia. The future burden of breast cancer is predicted to increase to over 3 million new cases and 1 million deaths by 2040. The implications of the migratory flows and population spike in Klang Valley piqued our interest in finding out more about female breast cancer awareness, particularly their breast cancer knowledge and knowledge, attitude, and practice (KAP) of breast self-examination (BSE).
Methods
A cross-sectional study was conducted between April to June 2021 on women who aged ≥ 20 years old and live in Klang Valley. A validated questionnaire of 61 questions about breast cancer awareness was distributed online (social media platform) and physical approaches (community pharmacy). The participant's overall KAP was categorized using Bloom's cut-off point. A KAP domain was considered sufficient if the score was ≥ 60% and insufficient if the score was < 60%. The Mann-Whiteny U test and Kruskal-Wallis H test were used to determine the differences in median. The relationships between KAP domains were measured using Spearman’s correlation test.
Results
A total of 491 responses were collected. We found that most participants had adequate breast cancer knowledge (67.8%) and BSE knowledge (80.5%) and positive attitude of BSE (97.1%). However, their BSE practice was extremely poor (72.9%), and forgetfulness was the main barrier. Young women had poorer KAP scores than older women. Significant correlations were found between breast cancer knowledge–BSE knowledge (r = 0.682, p < 0.005), breast cancer knowledge–BSE practice (r = 0.384, p < 0.005), BSE knowledge–BSE practice (r = 0.372, p < 0.005) and BSE attitude–BSE barrier (r = -0.380, p < 0.005).
Conclusion
BSE remains a viable and practical alternative screening method for Malaysian women. Overall, the participants have adequate knowledge and positive attitude, but implement transformational changes is needed address issues such as low understanding among young women and poor BSE practice to down-staging breast cancer in Malaysia.
CSCNN: Lightweight modulation recognition model for mobile multimedia intelligent information processing
Authors: Chen Jun , Huang Yiping , Zhang Ling , Si Guangzhen , Wang Juzhen 
Published: February 2024

Abstract

With the advancement of the Internet of Things, the importance of multimedia intelligent information processing technology is increasing. Faced with massive electromagnetic data and limited terminal equipment computing resources, previous technologies cannot meet the real-time decisionmaking requirements for processing short-term observations or burst signals in deployable systems. In this paper, our approach proposes the Deep Complex Separable Convolution (DCSC) operation by combining separable convolution operation and complex convolution operation. At the same time, to better preserve coupling information between channels and minimize the model size, we propose the Multilevel Separable Convolutional Residual Block (MSCRB). Based on the above two methods, we constructed the Complex Separable Convolutional Neural Network (CSCNN). This neural network significantly reduces the complexity of the deep learning model. The smallest network we constructed, CSCNN-Tiny, has a model size of 0.760M, which is only 6% of the size of MobileNet. With 0.815M Flops, it is 3.8% of MobileNet. However, it achieves a recognition accuracy of 50.97%, only 0.97% lower than MobileNet.