bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immunosuppression by tetrahydrobiopterin increases the proliferation of regulatory T-cells and mast cells and modulates the cytokine expression in a murine heart transplant model
Authors: Ebner Susanne , Texler Bernhard , Nardin Florian , Troppmair Maria R , Nguyen Anh Vu , Cardini Benno , Troppmair Jakob , Schäfer Georg , Thalhammer-Thurner Gudrun C , Nirtl Kerstin , Lackner Katharina , Alenina Natalia , Öfner Dietmar , Schneeberger Stefan , Watschinger Katrin , Brandacher Gerald , Werner Ernst R , Maglione Manuel 
Published: October 2024

Abstract

Administration of tetrahydrobiopterin (BH4) has been shown to attenuate acute allograft rejection in a murine heart transplantation model in a manner similar to that of cyclosporine A. However, its mechanism of action on immune cells remains largely unknown. A fully MHC-mismatched (C3H/He to C57BL/6) mouse heart transplant model was used in this study. The recipients were treated with BH4 or Cyclosporine A six days. The degree of acute rejection was assessed by histopathological analysis, splenocytes were analyzed by flow cytometry, and cytokine production was estimated based on the level of protein and RNA in sera and grafts and in vitro in T cell cultures. Proliferation of regulatory T cells and mast cells, suppressor capacity of Tregs, and MLR of T cells were conducted in vitro. Survival curves confirmed the significant improvement observed in the BH4-treated animals. BH4-treatment resulted in a substantial increase in Tregs and mast cells in the secondary lymphoid organs. In vitro assays showed increased proliferation of BH4-treated Tregs and mast cells. Cytokine production in vivo and in vitro in BH4-treated animals revealed an increase in the expression of IL-10, IL-5 and IL-4. BH4-dependent mast cell-derived tryptophan hydroxylase-1 could be excluded as a treatment target in recipient knockout mice. These data suggest that BH4 modulates the innate and adaptive immune systems, resulting in increased proliferation of regulatory T and mast cells accompanied by a modulation of anti-inflammatory cytokines.
Abrupt changes in heatwave evolution in Mediterranean Chile and California
Authors: Carrillo Hugo , Mendoza Mauro , Lambert Fabrice , Wout Elwin van ’t 
Published: October 2024

Abstract

Heatwaves are extreme weather events with significant impacts on natural ecosystems, human health, and socio-economic systems. While global trends indicate an increase in the frequency, duration, and intensity of heatwaves due to climate change, regional studies are essential to understand local variations and impacts. This study aims to address the gap in knowledge regarding the evolution of heatwaves in Central Chile and California, two regions with similar Mediterranean climates but located in different hemispheres.
We analyzed temperature data from meteorological stations in Central Chile and California over the past five decades. Using various heatwave definitions and indices, we quantified trends in heatwave frequency, duration, and intensity. The number of heatwave events per year in Central Chile increased by approximately one event every 15 years, while in California we register an average increase of one event per decade, although regional variations exist. These trends have accelerated over the last two decades, with abrupt changes in heatwave behavior detected around 2010 in both regions. We suggest that strong reductions in anthropogenic aerosol emissions around this time removed atmospheric aerosol cooling and may have abruptly amplified heatwaves post-2010.
These findings highlight the accelerating impact of changing climate conditions on heatwave characteristics in Central Chile and California, and indicate possible unintended consequences of air quality improvements. Our results underscore the urgent need for adaptive measures to mitigate the adverse effects of increasing heatwaves.
Evaluation of Mixed Chuihui (Modified Mortar) Material on the Chest and Abdomen of Leshan Giant Buddha
Authors: Sun Bo , Liang Yuyuan , Shi Wentao , Peng Ningbo , Wu Guopeng 
Published: October 2024

Abstract

As a traditional repair material, Chuihui has been maturely used in the restoration work of the Leshan Giant Buddha many times. Fundamentally, it is a kind of mortar processed by "hammering". Over the years, it is mainly divided into traditional Chuihui, mixed Chuihui and modified Chuihui. This study tested and evaluated the mixed Chuihui material on the chest and abdomen of the Leshan Giant Buddha in 2001. By measuring the thickness, surface hardness, density, and longitudinal wave velocity of the mixed Chuihui, and combining the results of X-ray diffraction analysis, infrared spectroscopy analysis, micro-drilling damping detection, micro-morphological characteristics, and mercury intrusion porosimetry, the macroscopic physical indicators and microscopic characteristics were analyzed and its performance was evaluated. The results show that among the three-layer structure (surface layer, middle layer, and cushion layer) of the mixed Chuihui material, the cushion layer has greater thickness and porosity, lower wave velocity and hardness, the lowest average drilling force value, the highest proportion of cracks, and the worst overall performance. At the same time, the existence of the hydration product C-S-H proves that there is a cement component in each layer of Chuihui. Since the surface layer of mixed Chuihui uses higher quality raw materials and is protected by carbonation, the physical and mechanical properties of the surface layer are at a relatively high level compared with the other two layers. Moreover, according to the order from air to bedrock, the mechanical properties of the three-layer structure of Chuihui material show a gradually decreasing trend. When encountering external damage or natural shedding, the Chuihui layer can act as a sacrificial layer and be damaged, thus avoiding damage to the bedrock. The strength of the surface layer also ensures its ability to resist weathering.
Uptake of heavy metals from aqueous media onto the blend of sodium alginate and kernel powder
Authors: Sardar Muhammad Hamza , Saddique Muhammad Tahir 
Published: October 2024

Abstract

Heavy metal poisoning is widely recognized as a serious problem for both the environment and human health. The damage caused by these metals has raised concerns for global public health and ecology, prompting a significant focus on developing effective materials for heavy metal removal. This study presents a method for creating an environmentally friendly adsorbent for removing metal ions from aqueous solutions, using sodium alginate/mango seed kernel blend beads (SA/MSK). The goal was to develop a low-cost, beneficial adsorbent by utilizing mango seed kernel (MSK), an agricultural waste product, as a resource to manufacture material for the removal of specific heavy metals. Adsorption, one of the most promising techniques, was employed in this work. Batch studies were conducted to examine the effects of pH, dosage, initial metal ion concentration, adsorbent particle size, and contact time on the percentage removal of Cd²⁺, Cu²⁺, and Pb²⁺ ions. FTIR, SEM, and XRD analyses demonstrated that carboxyl and hydroxyl functional groups were involved in the sorption of Cu²⁺, Cd²⁺, and Pb²⁺ ions. The efficacy of SA/MSK beads in eliminating metal ions from effluent samples showed that the beads were able to remove all three metal ions to varying degrees. Physicochemical and spectroscopic methods revealed that the binding sites involved were ether, carboxyl, hydroxyl, and amine groups. These findings suggest that SA/MSK beads hold great potential for applications in heavy metal removal and could become a sustainable method for removing metal ions from effluent.
The Synergistic effects and mechanism of recombinant viral vector-mediated co-expression plasmids stat1 and stat3-siRNA on glioma in vivo and in vitro
Authors: Hu Xin long , Li Hong , Zhang Guodong , Lin Chao , Huang Ping , Chen Xiufeng , Wan Fang , Dou Changwu , Ju Haitao 
Published: October 2024

Abstract

Objective
To investigate the Synergistic effects and mechanism of recombinant viral vector-mediated co-expression plasmids stat1 and stat3-siRNA on glioma in vivo and in vitro
Methods
We constructed the co-expression plasmid stat1/stat3-SiRNA and packaged it into lentivirus and adenovirus for cell and animal experiments. Real-time PCR and Western blot analyses were used to detect the expression of STAT1 and STAT3 at the gene and protein levels. CCK-8, TUNEL, flow cytometry, and cell scratching assays were established to detect the therapeutic effect of the co-expression plasmid stat1/stat3-SiRNA on glioma in vivo and in vitro, and we used transcriptome sequencing to further explore the possible mechanism.
Results
After we treated gliomas with the co-expression plasmid stat1/stat3-SiRNA, STAT1 increased and STAT3 decreased significantly in mRNA and protein expression levels, Compared with the single-gene stat1 and stat3-SiRNA groups, stat1/stat3-siRNA group inhibited the proliferation and migration of U251 cells, and the tumor growth in nude mice more significantly. The analysis of the transcriptome sequencing results suggested that changing multiple nodes in the FOXO signaling pathway may be the main mechanism for co-expression of lenti-stat1/stat3-SiRNA than the single genome stat1 or stat3-SiRNA to inhibit the proliferation of U251 cells and induce their apoptosis, but awaiting further research and discussion.
Conclusions
The co-expression plasmid stat1/stat3-siRNA inhibits the growth of glioma and induces its apoptosis more significantly than the single genome stat1 and stat3-siRNA. The possible mechanism is to change multiple nodes in the FOXO signaling pathway.
Exploring the Relationship Between Physical Activity and Multimorbidity: Insights from the CHARLS Database
Authors: Mou Chuan , Wang Zhihua , Ke Zhifei 
Published: October 2024

Abstract

Background
Physical activity has been widely recognized for its important role in preventing cardiovascular and other chronic diseases. However, the specific relationship between different levels of physical activity and various chronic diseases, including multimorbidity, remains unclear, which require further investigation.
Methods
This study utilized the China Health and Retirement Longitudinal Study (CHARLS) database to classify physical activity levels based on metabolic equivalents (MET). The analysis focused on the relationship between low, moderate, and high physical activity levels and various chronic diseases, as well as the co-occurrence of multiple diseases. Multivariable logistic regression models were employed to assess the association between different activity levels and the risk of chronic diseases, while stratified analyses explored the impact of demographic factors on these associations. Additionally, a restricted cubic spline (RCS) model was applied to investigate potential nonlinear relationships between total MET and chronic disease risks.
Results
The results showed that compared to low activity levels, moderate and high levels of physical activity significantly reduced the risk of cardiovascular diseases and respiratory diseases, with a nonlinear dose-response relationship. High levels of physical activity also significantly lowered the risk of multimorbidity, particularly the coexistence of three or more chronic diseases (OR = 0.55, 95% CI: 0.47, 0.65, P < 0.01). However, moderate activity levels were associated with increased risks of dyslipidemia and diabetes, while high levels of activity were linked to higher risks of arthritis and kidney diseases. Stratified analyses revealed that demographic factors influenced the association between physical activity and disease risk.
Conclusion
Moderate and high levels of physical activity provide significant protection against cardiovascular and respiratory diseases and effectively reduce the risk of multimorbidity. However, the increased risk of certain metabolic and joint diseases with higher activity levels warrants further attention. Future research should clarify the impact of physical activity on different populations and chronic diseases, with randomized controlled trials needed to verify causality.
Generative AI based Predictive Maintenance in Aviation: A Systematic Literature Review
Authors: Khan Zeeshan Ullah , Nasim Bisma , Rasheed Zeehasham 
Published: October 2024

Abstract

Predictive maintenance (PdM) is a critical tool in aviation, promoting sustainability, safety, and cost-effectiveness. However, a significant challenge in implementing predictive maintenance framework is limited run-to-failure data due to frequent preventive maintenance. Generative AI (GAI) offers a promising solution to this challenge by generating synthetic data, enabling more accurate predictions of aircraft system health. The recent surge in scientific publications exploring GAI's potential for aviation predictive maintenance emphasizes the need for a comprehensive review. This research addresses this gap by conducting a systematic literature review (SLR), employing an active learning open-source tool to thoroughly analyze papers sourced from four scientific databases. These papers focus on predictive maintenance of aircraft systems through generative AI models. The findings of this review examine various aspects of GAI-powered predictive maintenance, including its objectives, the diversity of models employed, areas of application, datasets used for model validation, and the prevailing challenges and emerging trends. The review identified that most commonly used GAI models in aircraft PdM are GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders) or combination of these models. However, knowledge sharing, model integration and specificity are the key challenges associated with the implementation of these models. This strong knowledge-base will be a valuable resource for researchers, engineers, and practitioners aiming to improve their knowledge and implementation of GAI-driven models for predictive maintenance in the aviation industry.
Arsenic and Heavy metals levels into edible fresh meat (chicken, goat, and beef) and associated health risks
Authors: Shah Syed Sayyam Abbas , Eqani Syed Ali Musstjab Akber Shah , Nawaz Ismat , Ali Nadeem , Rajah Nisreen , Rasheed Iqra , Ali Syeda Maria , Orif Muhammad I , Shen Heqing 
Published: October 2024

Abstract

The current study (very first) measured the concentrations (dry weight; µg/kg) of arsenic (As) and selected heavy metals (Cr, Ni, Mn, Pb, Cd, Cu, Zn) by using ICP-MS in muscle and liver samples of chicken, mutton, and beef from different areas (Peshawar, Islamabad, Gujrat, Lahore) of Pakistan. In general, the occurrence trend of studied toxic elements in liver and muscle samples were as follows: Zn > Cu > Mn > Cr > Ni > Pb > As > Cd. As, Cd, Pb (µg/kg) and Cu (mg/kg) were significantly higher in beef liver (110.2, 100, 358.6, and 115.1, respectively) than those of mutton (51.3, 63.3, 234.9 and 74.5) and chicken liver (41.3, 29.3, 115.5 and 11.3). On the other hand, As, Pb (µg/kg), and Zn (mg/kg) concentrations were significantly higher in the muscles of mutton (121.6, 247.7, 146.6, respectively) and beef (117.2,227.2 and 166.4) followed by chicken (44.5, 141.1, 41.3). Similarly, organ-wise levels of the studied toxic elements (particularly Mn, and Cu) were higher in liver samples than those of muscles of all types of animals except for As (high in mutton muscle) and Cr, Ni, Zn (high in beef muscle). Our results highlighted that beef (liver and muscle) is the most contaminated type of meat than those of mutton and chicken (liver and muscle). Correlation analysis and principal component analysis (PCA) highlighted that studied toxic metals exposure may be linked to the contaminated soil/dust (Mn, Pb, Cd, Ni), water (As, Cr, Pb) and food (Zn, Cu, Cd, Ni) at different locations of Indus floodplain. Chronic exposure of the studied toxic metals (HQ > 1 for As, Cr, Cu, and Zn) through meat (particularly beef liver and muscle) consumption may be harmful for human health and may pose significant threat to the consumer’s health.
QbD-Driven Development and Validation of an Optimized HPTLC Method for Simultaneous Estimation of Berberine and Conessine
Authors: Naik Archana , Chhaya Gadgoli , Yadav Sriniwas , Nagargoje Rutuja , Patil Siddhika 
Published: October 2024

Abstract

Berberine, an isoquinoline-derivative alkaloid from Berberis aristata, and conessine, an alkaloid found in the stem bark of Holarrhena antidysenterica, have long been used in traditional medicine to treat gastrointestinal and reproductive issues. This study focused on developing a high-performance thin-layer chromatography (HPTLC) method for the simultaneous quantification of berberine and conessine, optimized using a Quality by Design (QbD) approach. The method development involved the systematic optimization of critical method parameters (CMPs) such as mobile phase ratio, saturation time, distance travelled, and derivatizing agent concentration, using a Box-Behnken design. The critical analytical attributes (CAAs) evaluated included peak area and retardation factor as indicators of method robustness. Optimal chromatographic separation was achieved with a mobile phase of ethyl acetate, methanol, and diethyl amine in a ratio of 6.5:1.0:0.3 v/v on Silica gel 60GF 254 plates. Berberine and conessine were detected densitometrically at 350 nm and 620 nm, respectively, with Rf values of 0.22 and 0.85. The method was validated as per the ICH recommended conditions, which revealed high degree of linearity, accuracy, precision, sensitivity and robustness. The method was demonstrated to be simple, fast, accurate, resilient, and exact. Also, the method was applied for the estimation of berberine and conessine in inhouse formulations, which indicated no significant change in the retention time. In a nutshell, the studies demonstrated successful development of the HPTLC method for simultaneous estimation of berberine and conessine with improved understanding of the relationship among the influential variables for enhancing the method performance.
Revisiting the long-run and short-run relationship between economic growth, exchange rate, money supply, and government expenditure: empirical evidence from India using the NARDL approach.
Authors: Husain Shah , baig Imran Ali , Rana Minakshi , Khalid Bushra 
Published: October 2024

Abstract

The prior research that examined at how exchange rate fluctuations affected economic growth were based on the symmetric method, which predicted that the impact on GDP would be the same for both overvalued and undervalued exchange rates. However, recent research has shown that important economic variables like trade flows and economic growth are typically affected asymmetrically by the exchange rate. The primary aim of the present study is to examine the long term and short-term association among economic growth, exchange rate changes, money supply and government expenditure for a period of 1980-2022 in India. The study employed nonlinear autoregressive distributed lag model (NARDL) to examine the asymmetric relationship among the scrutinised variables. Furthermore, we used Granger causality test to check the direction of causal association. The results of NARDL confirm the long-term relationship among economic growth, exchange rate changes, money supply and government expenditure. The findings show that undervaluation affect economic growth negatively in the case of the Indian economy whereas overvaluation promotes it. Moreover, we found asymmetric impact of exchange rate change on economic growth in India. The Wald test confirms the asymmetrical relationship between exchange rate and economic growth for both short-run and long-run. The results of causality test show bidirectional causality among exchange rate, government expenditure and economic growth. While, one-way causal effects run from money supply to economic growth. The findings of the study have some policy implications. Exchange rate governing organisation should place a priority on restoring stability and work towards developing more robust exchange rates in order to achieve the goal of sustained economic growth and, ultimately, sustainable development
JEL: B22, CO1, E51, H50
Experimental Validation of Sparse Sensor Placement Optimization for Flight-By-Feel of a Delta Wing
Authors: Hollenbeck Alex C. , Grandhi Ramana V. , Pankonien Alexander M. 
Published: October 2024

Abstract

The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm is a data-reducing approach for extracting maximum information from a low-order sparse approximation of a dense dataset for use in continuous prediction of one or more system parameters. The SSPOP algorithm can work directly with discrete data, such as the calculated velocity at nodes in a computational fluid dynamics (CFD) model, and is simpler and faster to implement than conventional gradient-based optimization methods. This research is the first experimental validation of an SSPOP-selected design point (DP), or set of sensor locations, for a flight-by-feel (FBF) flow-sensing system on a wing. We evaluate the absolute and relative computational and experimental performance of five three-sensor DPs on a NACA 4415, 45-degree-swept delta wing for predicting the angle of attack (AoA) from airflow velocity and pressure measurements. The experimental results from artificial hair-cell airflow velocity sensors (AHS) qualitatively validate the computer models but are subject to large errors. The pressure sensor experimental results quantitatively validated the models, with the SSPOP DP error of 0.703 degrees AoA nearly matching the optimum DP error of 0.692 degrees, confirming that SSPOP finds a near-optimal sensor placement solution for flow sensors.