Hasil untuk "Science (General)"

Deema O. Qasrawi, Adriano M. C. Pimenta, Evgeniy V. Petrotchenko et al.

<b>Background:</b> Quantifying urinary catecholamines and metanephrines is essential for the clinical screening and diagnosis of neuroendocrine tumours. HPLC with electrochemical detection (HPLC-ECD) is commonly used for this type of analysis but requires extensive sample cleanup. Simple and rapid dilute-and-shoot LC–multiple-reaction monitoring (MRM)-MS assays have been developed for quantitating these analytes in urine but have not yet been validated according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. <b>Methods:</b> A simple dilute-and-shoot sample preparation without derivatization was used. C18 RP-UPLC-MRM-MS and positive-ion ESI were used, usually with two transitions per analyte being monitored. Certified deuterated internal standards were used for each analyte. <b>Results:</b> This assay was validated according to the CLSI C62-A guidelines, including accuracy/trueness, imprecision, sensitivity, specificity, carryover, stability, and linearity. The final MRM-MS method was compared to the established HPLC-ECD clinical chemistry reference method. The run time was reduced from 25 min to 5 min. <b>Conclusions:</b> A simple, robust, rapid, and cost-effective LC-MRM-MS assay for measuring urinary catecholamines and metanephrines was developed and validated according to the CLSI guidelines. This validated method requires minimal sample manipulation before analysis and provides sensitivity, specificity, and improved precision. The implementation of this assay in clinical laboratories will facilitate early and accurate diagnosis.

Rafeeq P. H. Ahmed, Onur Kanisicak, Perwez Alam

<b>Background</b>: The limited regenerative capacity of adult mammalian cardiomyocytes (CMs) poses a significant challenge for cardiac repair following myocardial infarction. In contrast to adult mammals, CMs in zebrafish and newt hearts retain a lifelong capacity for proliferation and cardiac regeneration. Likewise, neonatal mice exhibit a brief postnatal period, during which CMs retain the ability to proliferate and contribute to myocardial repair, which markedly diminishes within the first week of life. Emerging evidence indicates that adult CM cell cycle progression is critically influenced by oxidative stress. Adult mammalian CMs possess a high mitochondrial content to meet their substantial energy demands. However, this also leads to elevated reactive oxygen species (ROS) production, resulting in DNA damage and subsequent cell cycle arrest. We hypothesize that reducing the mitochondrial content in adult CMs will mitigate ROS production, thereby facilitating cell cycle progression. <b>Methods</b>: Adult CMs were isolated from adult rats (≥12 weeks old). To induce mitophagy, adult CMs were transfected with parkin-expressing plasmid and then treated with carbonyl cyanide 3-chlorophenylhydrazone (CCCP), a mitochondrial protonophore, for 7 days. Post-treatment assessments included the quantification of adult CM proliferation, mitochondrial content, and ROS levels. <b>Results</b>: CCCP-treated adult CMs exhibited a significant increase in proliferation markers, including EdU incorporation, KI67, phospho-histone H3, and Aurora B. Furthermore, CCCP treatment significantly reduced the mitochondrial content, as evidenced by decreased MitoTracker, TMRM, and Tom20 staining compared to controls. This was accompanied by electron microscopy analysis, which showed a significant reduction in the mitochondrial number in the adult CM after CCCP treatment. Moreover, our results also demonstrate a marked reduction in oxidative stress, demonstrated by lower 123-dihydro-rhodamine (123-DHR), CellROX signals, and VDAC. <b>Conclusions</b>: Our findings demonstrate that CCCP-mediated mitochondrial depletion reduces oxidative stress and promotes cell cycle re-entry in adult CM. This study provides direct experimental evidence and substantiates the role of elevated mitochondria and ROS levels in adult CM cell cycle exit.

Wentong Chen, Mengxiao Ge, Shuangyi Sun et al.

Abstract As critical precursors to colorectal cancer (CRC), high-risk colorectal adenomas (HR-CRAs) lack effective chemopreventive strategies beyond endoscopic resection. We previously established a standardized protocol for culturing patient-derived HR-CRA organoids (HR-CRA-PDOs), creating a robust platform for targeted drug discovery in colorectal premalignancy. Bioinformatics investigation was conducted to unveil the significant dysregulation of lipid metabolism in HR-CRAs. HR-CRA-PDOs were primarily cultured and exposed to gradient concentrations of atorvastatin, with drug responses evaluated with high-throughput and high-content imaging and ATP-based viability assays. Parallel in vivo validation utilized AOM/DSS-induced mouse model under either normal or high-fat diets. Histological and molecular analyses were conducted to evaluate adenoma dynamics, apoptosis, and lipid metabolism-related gene and protein expressions. Bioinformatics analysis of GEO database (GSE100179 and GSE161277) revealed that HR-CRAs are characterized by dysregulated lipid metabolism, particularly through the upregulation of fatty acid metabolism pathways. In vitro, atorvastatin significantly inhibited HR-CRA-PDO growth in a dose-dependent manner via apoptosis induction and proliferation arrest. Mechanistically, atorvastatin treatment led to significant alterations of gene expression in lipid metabolism pathways including ACOX1, ACOX2, FABP2, NRG1, PPAR-α and SREBF1, concomitant with stemness marker suppression in HR-CRA-PDOs. In vivo, atorvastatin markedly reduced CRA burden in AOM-DSS-induced mouse model, particularly demonstrating enhanced efficacy in high-fat diet contexts. This translational study establishes atorvastatin’s dual mechanism in metabolic reprogramming and stemness inhibition, suggesting its potential as a therapeutic strategy for CRA prevention and treatment.

Manuel Cuerno, Luis Guijarro, Rosa María Arnaldo Valdés et al.

Analyzing flight trajectory data sets poses challenges due to the intricate interconnections among various factors and the high dimensionality of the data. Topological Data Analysis (TDA) is a way of analyzing big data sets focusing on the topological features this data sets have as point clouds in some metric space. Techniques as the ones that TDA provides are suitable for dealing with high dimensionality and intricate interconnections. This paper introduces TDA and its tools and methods as a way to derive meaningful insights from ATM data. Our focus is on employing TDA to extract valuable information related to airports. Specifically, by utilizing persistence landscapes (a potent TDA tool) we generate footprints for each airport. These footprints, obtained by averaging over a specific time period, are based on the deviation of trajectories and delays. We apply this method to the set of Spanish' airports in the Summer Season of 2018. Remarkably, our results align with the established Spanish airport classification and raise intriguing questions for further exploration. This analysis serves as a proof of concept, showcasing the potential application of TDA in the ATM field. While previous works have outlined the general applicability of TDA in aviation, this paper marks the first comprehensive application of TDA to a substantial volume of ATM data. Finally, we present conclusions and guidelines to address future challenges in the ATM domain.

Mingrong Wang, Longnan Ma

This paper examines the impact of import competition on skill premium and the moderating effect of labor market flexibility on it, using panel data from 30 provinces in China from 2010 to 2019. A dynamic panel threshold model with instrumental variables is employed to address the endogeneity problem and to identify the nonlinear moderating effect of labor market flexibility. The results show the following: (1) Import competition has a promoting effect on skill premium, and this effect declines from eastern to western regions in China. (2) The import competition increases the skill premium through the channels of enhancing regional innovation capacity and promoting industrial upgrading and rationalization. (3) There exists a significant threshold effect in the moderating effect of labor market flexibility. When labor market flexibility surpasses the threshold value of 1.330, the enhancing effect of import competition on the skill premium is alleviated, facilitating labor reallocation and wage adjustment. The integration of labor market flexibility into the globalization–inequality debate extends the existing literature for providing a new understanding of the mechanisms behind the skill premium. The policy implications are that targeted labor market reforms are essential for mitigating wage differentials between skilled and unskilled workers arising from intensified import competition.

Haoyue Zhang, Dong Ye, Peng Xu et al.

Accurately calibrating the center-of-mass (CoM) offset between the spacecraft (SC) and the inertial sensor test mass (TM) is crucial for space-based gravitational-wave (GW) antennas, such as LISA and Taiji. Current calibration methods require additional spacecraft maneuvers that disrupt science data continuity and inter-satellite links, compromising the coherence of gravitational wave signals. Here, we present a maneuver-free calibration scheme that directly estimates the CoM offset vector using only standard science-mode measurements from inertial sensors, interferometers, and differential wavefront sensors. By embedding the CoM offset induced coupling acceleration as an extended state in a model-based adaptive Kalman filter, we achieve estimation accuracy of 0.01-1.5 mm across all axes with a maximum error below 1%. This approach enables continuous, high-precision calibration during nominal observation runs, ensuring continuous and coherent gravitational wave data collection while maintaining the required precision, and also facilitating advanced DFACS functions such as performance evaluations and fault diagnosis. For LISA-like missions, where data continuity is paramount for detecting faint gravitational wave signals, this method will enhance scientific output and reliability.

Emilio Porcu, Roy El Moukari, Laurent Najman et al.

This manuscript provides a systemic and data-centric view of what we term essential data science, as a natural ecosystem with challenges and missions stemming from the fusion of data universe with its multiple combinations of the 5D complexities (data structure, domain, cardinality, causality, and ethics) with the phases of the data life cycle. Data agents perform tasks driven by specific goals. The data scientist is an abstract entity that comes from the logical organization of data agents with their actions. Data scientists face challenges that are defined according to the missions. We define specific discipline-induced data science, which in turn allows for the definition of pan-data science, a natural ecosystem that integrates specific disciplines with the essential data science. We semantically split the essential data science into computational, and foundational. By formalizing this ecosystemic view, we contribute a general-purpose, fusion-oriented architecture for integrating heterogeneous knowledge, agents, and workflows-relevant to a wide range of disciplines and high-impact applications.

Karthikeyan K, Philip Wu, Xin Tang et al.

The Science Consultant Agent is a web-based Artificial Intelligence (AI) tool that helps practitioners select and implement the most effective modeling strategy for AI-based solutions. It operates through four core components: Questionnaire, Smart Fill, Research-Guided Recommendation, and Prototype Builder. By combining structured questionnaires, literature-backed solution recommendations, and prototype generation, the Science Consultant Agent accelerates development for everyone from Product Managers and Software Developers to Researchers. The full pipeline is illustrated in Figure 1.

Akane Yamazaki, Makiko Tanaka

Ergothioneine (EGT) is abundant in fungi such as mushrooms and certain bacteria, and is known for its strong antioxidant properties. EGT has also been implicated in aging and disease, with the expectation that maintaining its concentration in the body can extend a healthy lifespan. Therefore, this study aims to investigate the relationship between dietary habits and EGT levels among men and women aged 40 and above. The goal was to identify the dietary habits that could increase EGT levels. The investigation included physical measurements, blood tests, and a BDHQ questionnaire. Regarding food intake, a positive correlation was observed between Ergothioneine (EGT) and the consumption of mushrooms, legumes, and tofu/aburaage among all participants. Furthermore, regarding nutrient intake, a positive correlation was found between the EGT levels and the consumption of daidzein and genistein, which are nutrients primarily found in soybeans. Additionally, among females, negative correlations were found between blood EGT concentrations and serum triglycerides, along with positive correlations with HDL cholesterol. Given that Ergothioneine (EGT) is abundant in mushrooms, the correlations observed with mushrooms in the present study are reasonable. Although EGT has been found to some extent in certain types of legumes, previous research suggests that soybeans contain negligible amounts of EGT. This suggests a potential association with the soybean products consumed in the study region. From these findings, it was observed that a higher intake of mushrooms, legumes, tofu, and aburaage correlated with higher EGT blood concentrations, which are expected to contribute to the suppression of various diseases associated with lifestyle-related illnesses and aging, thereby potentially extending the healthy lifespan. Furthermore, EGT levels may be strongly associated with serum triglyceride and HDL cholesterol levels.

Chunhong Dong, Bao-Zhong Wang

Indrajit Sen

Abstract Non-normalizable states are difficult to interpret in the orthodox quantum formalism but often occur as solutions to physical constraints in quantum gravity. We argue that pilot-wave theory gives a straightforward physical interpretation of non-normalizable quantum states, as the theory requires only a normalized density of configurations to generate statistical predictions. In order to better understand such states, we conduct the first study of non-normalizable solutions of the harmonic oscillator from a pilot-wave perspective. We show that, contrary to intuitions from orthodox quantum mechanics, the non-normalizable eigenstates and their superpositions are bound states in the sense that the velocity field $$v_y \rightarrow 0$$ v y → 0 at large $$\pm y$$ ± y . We argue that defining a physically meaningful equilibrium density for such states requires a new notion of equilibrium, named pilot-wave equilibrium, which is a generalisation of the notion of quantum equilibrium. We define a new H-function $$H_{pw}$$ H pw , and prove that a density in pilot-wave equilibrium minimises $$H_{pw}$$ H pw , is equivariant, and remains in equilibrium with time. We prove an H-theorem for the coarse-grained $$H_{pw}$$ H pw , under assumptions similar to those for relaxation to quantum equilibrium. We give an explanation of the emergence of quantization in pilot-wave theory in terms of instability of non-normalizable states due to perturbations and environmental interactions. Lastly, we discuss applications in quantum field theory and quantum gravity, and implications for pilot-wave theory and quantum foundations in general.

W. Madushan Fernando, Amila Thibbotuwawa, H. Niles Perera et al.

The Vehicle Routing Problem (VRP) represents a thoroughly investigated domain within operations research, yielding substantial cost savings in global transportation. The fundamental objective of the VRP is to determine the optimal route plan that minimizes the overall distance traveled. This study employs VRP to address the challenge of distributing fresh agricultural products within retail chains. It introduces an integrated bi-objective VRP model that concurrently optimizes resource allocation, order scheduling, and route planning. The proposed model incorporates two objective functions with the goals of minimizing total distribution costs and ensuring timely product deliveries to retail outlets. Real-world characteristics are integrated to enhance practical applicability. All solution algorithms and the developed VRP model undergo testing using data from one of Sri Lanka's largest retail chains. Numerical experiments showcase the efficiency of the proposed algorithm in solving real-world VRP problems. Moreover, the proposed VRP model achieves a 19% reduction in daily distribution costs, including a 24% saving in fuel costs. This not only provides financial benefits but also contributes to the reduction of the carbon footprint of retail chains. The model ensures on-time deliveries to 95% of retail outlets, which is crucial for maintaining the quality of fresh food. The findings of this study underscore the significant cost savings, enhanced sustainability, and improved quality associated with the efficient distribution of fresh agricultural products within retail chains.

Yuwei Yin, Zhixian Tang, Huachun Weng

Abstract Deep Self-Attention Network (Transformer) is an encoder–decoder architectural model that excels in establishing long-distance dependencies and is first applied in natural language processing. Due to its complementary nature with the inductive bias of convolutional neural network (CNN), Transformer has been gradually applied to medical image processing, including kidney image processing. It has become a hot research topic in recent years. To further explore new ideas and directions in the field of renal image processing, this paper outlines the characteristics of the Transformer network model and summarizes the application of the Transformer-based model in renal image segmentation, classification, detection, electronic medical records, and decision-making systems, and compared with CNN-based renal image processing algorithm, analyzing the advantages and disadvantages of this technique in renal image processing. In addition, this paper gives an outlook on the development trend of Transformer in renal image processing, which provides a valuable reference for a lot of renal image analysis.

Feng Xiong, Xinguo Yu, Hon Wai Leong

This paper explores the transformative role of artificial intelligence (AI) in enhancing scientific research, particularly in the fields of brain science and social sciences. We analyze the fundamental aspects of human research and argue that it is high time for researchers to transition to human-AI joint research. Building upon this foundation, we propose two innovative research paradigms of human-AI joint research: "AI-Brain Science Research Paradigm" and "AI-Social Sciences Research Paradigm". In these paradigms, we introduce three human-AI collaboration models: AI as a research tool (ART), AI as a research assistant (ARA), and AI as a research participant (ARP). Furthermore, we outline the methods for conducting human-AI joint research. This paper seeks to redefine the collaborative interactions between human researchers and AI system, setting the stage for future research directions and sparking innovation in this interdisciplinary field.

Ковалев Дмитрий Петрович, Ковалев Петр Дмитриевич, Зарочинцев Виталий Сергеевич et al.

Рассматриваются результаты изучения длинноволновых движений с периодами более 20 ч на шельфе юго-западного побережья о. Сахалин с использованием полученных в натурных экспериментах временных серий колебаний уровня моря с дискретностью 1 с и продолжительностью от 4 до 6 мес. Спектральный анализ временных серий колебаний уровня моря для диапазона периодов от 8 до 200 ч выявил наличие длинноволновых процессов с периодами от 26.1 до 46.7 ч, которые значительно превышают инерционный период 16.48 ч. Численное моделирование шельфовых волн для экспоненциально выпуклых профилей морского дна, проведенное с использованием дисперсионного соотношения В.Т. Бухвальда и Дж.К. Адамса для волн континентального шельфа, показало, что обнаруженные волновые процессы с периодами от 31.2 ч до 46.7 ч являются шельфовыми волнами. Их амплитуды увеличиваются во время штормов; показана возможность передачи энергии от атмосферных возмущений шельфовым волнам, которые вносят вклад в формирование уровня моря, что подтверждает ранее сделанное предположение. Путем расчета разности фаз шельфовых волн на расстоянии 12.4 км между Невельском и Горнозаводском, наблюдаемых и определенных по теоретической модели, установлено, что вторая мода шельфовой волны с частотой 0.152 цикл/ч близка к теоретической. Регистрируемая в Ильинском и Горнозаводске волна с периодом 26.1 ч при расстоянии между пунктами 173.6 км не может быть шельфовой, а является волной Кельвина. Это подтверждено рассчитанной дисперсионной диаграммой, согласно которой длина волны около 689 км хорошо соответствует разности фаз для расстояния Ильинский–Горнозаводск. Установлено, что шельфовые волны, одним из механизмов генерации которых является напряжение ветра вдоль берега, имеют разные амплитуды в летнее и зимнее время, что обусловлено сезонным направлением вдольберегового ветра. В летний период направления распространения шельфовых волн и ветра противоположны, что ослабляет шельфовые волны.

Yingjie Wang, Lulu Wang, Fuli Hu et al.

High-mobility group box 1 (HMGB1), a member of damage-associated molecular patterns (DAMPs), is involved in the immune regulation of several infectious diseases. <i>Mycoplasma gallisepticum</i> (MG) infection is proved to cause an abnormal immune response, but the role of HMGB1 in MG-induced chronic respiratory disease (CRD) is unclear. In this study, we found that HMGB1 was released from the nucleus to the extracellular in macrophages upon infection with MG. Extracellular HMGB1 bound to TLR2 activating the NF-κB pathway triggering a severe inflammatory storm and promoting the progression of MG infection. More importantly, TLR4 could be activated by HMGB1 to trigger immune disorders after TLR2 was silenced. This disease process could be interrupted by ethyl pyruvate (EP) inhibition of HMGB1 release or glycyrrhizic acid (GA). Furthermore, treatment of MG-infected chickens with GA significantly alleviated immune organ damage. In conclusion, we demonstrate that HMGB1 is secreted extracellularly to form an inflammatory environment upon MG infection, triggering a further cellular inflammatory storm in a positive feedback approach. Blocking MG-induced HMGB1 release or suppression downstream of the HMGB1-TLR2/TLR4 axis may be a promising novel strategy for the treatment of CRD. Furthermore, this study may provide a theoretical reference for understanding non-LPS-activated TLR4 events.

Haosen Ge, In Young Park, Xuancheng Qian et al.

High-quality text data has become an important data source for social scientists. We have witnessed the success of pretrained deep neural network models, such as BERT and RoBERTa, in recent social science research. In this paper, we propose a compact pretrained deep neural network, Transformer Encoder for Social Science (TESS), explicitly designed to tackle text processing tasks in social science research. Using two validation tests, we demonstrate that TESS outperforms BERT and RoBERTa by 16.7% on average when the number of training samples is limited (<1,000 training instances). The results display the superiority of TESS over BERT and RoBERTa on social science text processing tasks. Lastly, we discuss the limitation of our model and present advice for future researchers.

Aletta Lucia Meinsma, Sanne Willemijn Kristensen, W. Gudrun Reijnierse et al.

Researchers point to four potential issues related to the popularisation of quantum science and technology. These include a lack of explaining underlying quantum concepts of quantum 2.0 technology, framing quantum science and technology as spooky and enigmatic, framing quantum technology narrowly in terms of public good and having a strong focus on quantum computing. To date, no research has yet assessed whether these potential issues are actually present in popular communication about quantum science. In this content analysis, we have examined the presence of these potential issues in 501 TEDx talks with quantum science and technology content. Results show that while most experts (70%) explained at least one underlying quantum concept (superposition, entanglement or contextuality) of quantum 2.0 technology, only 28% of the non-experts did so. Secondly, the spooky/enigmatic frame was present in about a quarter of the talks. Thirdly, a narrow public good frame was found, predominantly by highlighting the benefits of quantum science and technology (found in over 6 times more talks than risks). Finally, the main focus was on quantum computing at the expense of other quantum technologies. In conclusion, the proposed frames are indeed found in TEDx talks, there is indeed a focus on quantum computing, but at least experts explain underlying quantum concepts often.

K. Goodpaster, Omolola A. Adedokun, G. Weaver

Rural school districts often struggle with attracting and retaining high-quality teachers, especially in science subject areas. However, little is known about STEM in-service teachers’ lived experiences of rural teaching as they relate to retention. In this phenomenographical study, six rural in-service science teachers were interviewed regarding their perceptions of the benefits and challenges of teaching in rural schools in general, and teaching science subjects in particular. Community interactions, professional development, and rural school structures emerged as three key factors related to rural teacher retention. Participants viewed each of these factors as having both positive and negative aspects. Findings from this study confirm existing literature regarding rural teaching, in general, but provide additional insight into the complexities of rural science teaching, in particular. Implications for rural teacher preparation, recruitment, and retention are discussed.

Chih-Ping Chen, Hsiu-Ting Tsai, Schu-Rern Chern et al.

Objective: We present prenatal diagnosis of mosaicism for double aneuploidy of 47, XXY and trisomy 7 (48,XXY,+7) at amniocentesis in a pregnancy with a favorable outcome. Case report: A 33-year-old woman underwent amniocentesis at 17 weeks of gestation because of an increased risk for Down syndrome in maternal serum screening. Amniocentesis revealed a karyotype of 48,XXY,+7[8]/46,XY[16]. Simultaneous array comparative genomic hybridization (aCGH) analysis on uncultured amniocytes revealed the result of arr [GRCh37] (7) × 3 [0.54], (X) × 2 [0.52], (Y) × 1, compatible with trisomy 7 mosaicism and Klinefelter syndrome mosaicism. The parental karyotypes and prenatal ultrasound findings were normal. Repeat amniocentesis performed at 23 weeks of gestation revealed a karyotype of 48,XXY,+7[13]/46,XY[7]. Simultaneous molecular cytogenetic analyses on uncultured amniocytes revealed 30% mosaicism for 48,XXY,+7 by aCGH and 37% (37/100 cells) mosaicism for trisomy 7 and disomy X by interphase fluorescence in situ hybridization (FISH) analysis. Polymorphic DNA marker analysis excluded uniparental disomy (UPD) 7 and indicated a maternal origin of the chromosome aberration. The pregnancy was continued to 39 weeks of gestation, and a 3070-g healthy male baby was delivered. The cord blood had a karyotype of 46,XY, the umbilical cord had a karyotype of 48,XXY,+7[3]/46,XY[37], and the placenta had a karyotype of 48,XXY,+7. At age one month, the neonate was phenotypically normal, and interphase FISH analysis revealed 4.8% (5/105 cells) mosaicism on buccal mucosal cells and 8.9% (8/90 cells) mosaicism on urinary cells for trisomy 7 and disomy X, compared with 2% in normal control. Interphase FISH analysis on buccal mucosal cells at age two months revealed normal findings in 100/100 cells. Conclusion: Mosaic 48,XXY,+7 at amniocentesis without UPD 7 can be associated with a favorable fetal outcome. Cytogenetic discrepancy between cultured amniocytes and uncultured amniocytes may occur in mosaic 48,XXY,+7 at amniocentesis.