bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Al-Qur'an Memorization Techniques Based on Computer File Models: Learning Innovation in Islamic Education
Authors: Idawati Khoirotul , Hanifudin Hanifudin
Published: November 2024

This study aims to develop an innovative Qur'an memorization technique by utilizing a computer file model in the context of Islamic education. The method used is Research and Development (RnD), which includes needs analysis, design, development, and evaluation of learning products. The results of the study indicate that this technique is effective in improving students' understanding and memorization abilities, thanks to the integration of creative elements such as imagination, visualization, association, and the use of color and music. Students involved in this technology-based learning reported increased motivation and interest in memorizing the Qur'an. This finding implies that the use of technology in the teaching and learning process can enrich traditional methods, making them more relevant to the development of the times and the needs of the younger generation. This method is expected to be adopted more widely in Qur'an education to encourage the effectiveness and efficiency of memorization
Applying deep learning and the ecological home range concept to document the spatial distribution of Atlantic salmon parr (Salmo salar L.) in experimental tanks
Authors: Kumaran Santhosh K. , Solberg Lars E. , Izquierdo-Gomez David , Cañon-Jones Hernan A. , Mage Ingrid , Noble Chris
Published: November 2024

Auditing fish welfare within the aquaculture research community relies on the thorough monitoring of outcome- (biotic) and input-based (e.g., abiotic) elements. The community utilises operational and laboratory-based welfare indicators (i.e., OWIs and LABWIs) as fit-for-purpose tools to help with that task. Incorporating behavioural auditing in this toolbox can sometimes be challenging because sourcing quantitative data is often labour intensive, and it can be a time-consuming process. Digitalization of this auditing via the use of computer vision and artificial intelligence can help automate the monitoring process, help gather continuous quantitative data and help process optimisation and the decision-making process. This study i) adapts the DeepLabCut framework, based on computer vision and machine learning, to obtain pose estimation of Atlantic salmon parr under replicated experimental conditions, ii) quantifies the fish spatial distribution through a toolbox of metrics inspired by the ecological concepts home range and core area, and iii) applies it to inspect behavioural variability in and around feeding. These results demonstrate that the aforementioned methodology can automate the auditing of i) fish detection, ii) spatial distribution of fish in tanks and iii) the variability of spatial distribution before, during and after feeding within and between tanks and days. This can provide stakeholders with valuable information on how the fish use their rearing environment and can be used to inspire further development of technologies for behavioural auditing of fish in research settings.
The control of magnetization reversal by tuning the interlayer exchange interaction in magnetic multilayers
Authors: Yu Seunghoon , Park Jinhyeok , Jo Yonghwan , Kim Woojong , Kim Hyeonsu , Kim Mingu , Jung Myung-Hwa , Rhie Kungwon , Lee Kyujoon
Published: November 2024

The interest of noncollinear spin structures in magnetic multilayers has recently gained a lot of interest in spintronics due to the observation of unique phenomena in these systems. In magnetic multilayers coupled by the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction the study of noncollinear interactions has gained interest. In this paper, we study the magnetization reversal of two magnetic layers with different magnetic anisotropy directions coupled by the RKKY interaction. We have chosen Pt/Co/Ru/Co40Fe40B20 structures where the Pt/Co show perpendicular magnetic anisotropy and CoFeB show an in-plane magnetic anisotropy.
Simplified radar architecture based on information metasurface
Authors: Cui Tie Jun , Wang Si Ran , Chen Zhan Ye , Chen Shao Nan , Dai Jun Yan , Zhang Jun Wei , Qi Zhen Jie , Wu Lijie , Sun Meng Ke , Zhou Qunyan , Li Hui Dong , Luo Zhangjie , Cheng Qiang
Published: November 2024

Modern radar typically employs a chain architecture that consists of radio-frequency (RF) and intermediate frequency (IF) units, baseband digital signal processor, and information display. However, this architecture often results in high costs, significant hardware demands, and integration challenges. Here we propose a simplified radar architecture based on space-time-coding (STC) information metasurfaces. With their powerful capabilities to generate multiple harmonic frequencies and customize their phases, the STC metasurfaces play a key role in chirp signal generation, transmission, and echo reception. Remarkably, the receiving STC metasurface can implement dechirp processing directly on the RF level and realize the digital information outputs, which are beneficial to lower the hardware requirement at the receiving end while potentially shortening the time needed for conventional digital processing. As a proof of concept, the proposed metasurface radar is tested in a series of experiments for target detection and range/speed measurement, yielding results comparable to those obtained by conventional methods. This study provides valuable inspiration for a new radar system paradigm to combine the RF front ends and signal processors on the information metasurface platform that offers essential functionalities while significantly reducing the system complexity and cost.
Academic self-efficacy and perceived stressors for surgical practice in nursing students: A descriptive and correlational design
Authors: Ozsaker Esma , Aykut Zuleyha , Doruker Nihal Celikturk , Koze Burcak Sahin , Gecit Sinem
Published: November 2024

Background: In high-stress surgical settings, it's crucial to recognize nursing students' academic self-confidence and the stressors they perceive. This understanding helps them effectively navigate their educational journey and cultivate a strong professional identity.
Methods: This study aimed to determine the relationship between nursing students' academic self-efficacy and perceived stressors for professional practice in surgical clinics. The study design is descriptive and correlational. A total of 284 undergraduate nursing students practicing in surgical clinics at a university in Izmir province were recruited during the 2022-2023 academic year. A Personal Information Form, the Academic Nurse Self-Efficacy Scale (ANSES), and the Nursing Students' Perceptions of Clinical Stressors Scale (NSPCSS-TR) were used to collect data. Descriptive statistics, Mann-Whitney U test, Kruskal-Wallis test, and Spearman correlation analysis were used to analyze the data.
Results: The mean age of the students included in the study was 21.02±1.52 years. The mean total score of the ANSES was 51.50±6.88 and the mean total score of the NSPCSS-TR was 82.98±15.58. There was no statistically significant relationship between the ANSES and NSPCSS-TR scores (r:-0.022, p:0.711). It was found that there was a statistically significant positive weak relationship between the ANSES sociability sub-dimension score and the NSPCSS-TR academic performance of the instructor sub-dimension score (r:0.190, p:0.001). It was found that there was a statistically significant negative weak relationship (r:-0.163, p:0.006) between ANSES external emotion management subscale score and NSPCSS-TR inappropriate situations in the clinical environment subscale score.
Conclusions: This study found that nursing students' perceptions of academic self-efficacy and clinical stressors were high. It is recommended that programs aimed at improving the academic self-efficacy of nursing students should be implemented, that clinical practice should be emphasized as an important part of nursing education and that comprehensive studies should be conducted to reduce perceived stress in surgical clinics.
Transcriptomic and Physiological Insights into Auxin-Mediated Root Growth and Potassium Uptake in Tobacco Under Low- Potassium Stress
Authors: Guan Kunhao , Li Yingying , Zhang Yuyin , Yang Jie , Ge Zixuan , Dai Xiaoyan
Published: November 2024

Background
Improving plant potassium uptake efficiency is of great significance for agricultural production. Auxin, as a key plant hormone, promotes root growth activity and enhances the plant's ability to absorb and accumulate mineral nutrients. To investigate the role of auxin in root growth and potassium uptake mechanisms under low-potassium stress, this study utilized tobacco as a model plant and conducted hydroponic experiments.
Results
Low-potassium stress significantly impaired root development and potassium uptake in tobacco plants. Under these conditions, exogenous IAA enhanced root development and increased potassium uptake, while NPA inhibited root growth and adversely affected potassium absorption and retention. Transcriptome sequencing under low-potassium conditions identified 8,381 differentially expressed genes (DEGs) between the two treatment groups, which were primarily enriched in pathways related to photosynthesis-antenna proteins, photosynthesis, plant hormone signal transduction, and the MAPK signaling pathway. Analysis of DEGs associated with auxin signaling, potassium ion channels, transporters, and transcription factors revealed several key genes involved in the response to low-potassium stress, including KUP6, IAA14, ARF16, PIN1, SKOR, NPF7.3, and AP2/ERF. Notably, KUP6 was upregulated following IAA treatment and downregulated with NPA, indicating that this potassium ion transporter gene plays a crucial role in the auxin-mediated alleviation of low-potassium stress in tobacco, likely linked to endogenous auxin levels
Conclusions
Our research reveals that potassium deficiency impairs root development and uptake in tobacco, and auxin plays a critical role in mitigating this stress. This study highlights auxin’s regulatory function in enhancing root growth and potassium absorption under low-potassium conditions, offering insights into the molecular mechanisms of potassium stress response
Arterial pulsations and transmantle pressure synergetically drive glymphatic flow
Authors: Nozaleda Guillermo L. , Coenen Wilfried , Haughton Victor , Sánchez Antonio L.
Published: November 2024

Clearance of waste material from the brain by the glymphatic system results from net flow of cerebrospinal fluid (CSF) through perivascular spaces surrounding veins and arteries. In periarterial spaces, this bulk flow is directed from the cranial subarachnoid space towards the brain’s interior. The precise pumping mechanism explaining this net inflow remains unclear. While in vivo experiments have shown that the pulsatile motion in periarterial spaces is synchronized with arterial pulsations, peristalsis alone has been deemed insufficient to explain bulk flow. In this study we examine an alternative mechanism based on the interaction between arterial pulsations and fluctuations in transmantle pressure. Previously studied using pressure data from a hydrocephalus patient, this mechanism is analyzed here in healthy subjects using in vivo flow measurements obtained via phase-contrast magnetic resonance imaging. Arterial pulsations are derived from flow-rate measurements of arterial blood entering the cranial cavity, while transmantle-pressure fluctuations are computed using measurements of CSF flow in the cerebral aqueduct. The two synchronized waveforms are integrated into a canonical multi-branch model of the periarterial spaces, yielding a closed-form expression for the bulk flow. The results confirm that the dynamic interactions between arterial pulsations and transmantle pressure are sufficient to generate a positive inflow along periarterial spaces.
PnNAC03 from Panax notoginseng Functions in Positively Regulating Saponins and Lignin Biosynthesis During Cell Wall Formation
Authors: Zhang Xiaoqin , Huang Yuying , Shi Yue , Wang Xin , Chen Wenqin , Amu Laha , Wang Baowei , Pen Zhenyu , Wang Xiaohui , Wei Shengli
Published: November 2024

NAC transcription factor family protein play an important role in modulation of secondary metabolites biosynthesis. Saponins are the major bioactive compounds for Panax notoginseng which is a world-famous medicinal plant, and possess multiple pharmacological activities. Secondary cell wall play crucial roles in P.notoginseng growth and stress resistance. However, the investigations on NAC transcription factors in regulation of saponin biosynthesis and secondary cell wall formation remain elusive. In this study, we cloned and characterized a NAC transcription factor, PnNAC03, which is nuclear-localized protein and exhibits transcriptional activation activity. Inhibition of PnNAC03 with RNAi method in P. notoginseng calli resulted in a significant reduction in the content of saponin and the expression of the saponin biosynthetic genes, including PnSS, PnSE, and PnDS. Additionally, PnNAC03 was demonstrated to bind to the promoters of these genes and thereby enhancing their expression. Furthermore, overexpression of PnNAC03 in Arabidopsis thaliana led to the increase of secondary cell wall thickness and lignin content, and upregulation of the expression of AtPAL and AtC4H. RNAi-mediated silencing of PnNAC03 in P. notoginseng further confirmed its role in lignin biosynthesis, as lignin content and the expression levels of PnPAL and PnC4H were significantly lowered. Furthermore, PnNAC03 could directly bind to the promoters of PAL and C4H in both A. thaliana and P. notoginseng. Collectively, our results highlight the dual regulatory role of PnNAC03 in promoting both saponin biosynthesis and lignin accumulation, providing valuable insights for the molecular breeding of P. notoginseng.
Concentration-dependent effects of melatonin: physiological and metabolic processes in Pfaffia glomerata plants grown in vitro
Authors: Silva José V. S. , Silva Tatiane D. , Felipe Sérgio H. S. , Batista Diego S. , Henschel Juliane M. , Fortini Evandro A. , Farias Letícia M. , Leite João P. V. , Almeida Michelle M. V. , Machado Kleiton L. G. , Otoni Wagner C.
Published: November 2024

Melatonin is a multifunctional molecule active in various metabolic processes, influencing the accumulation of bioactive metabolites in medicinal plants such as Pfaffia glomerata. This species has pharmacological and medicinal properties, mainly due to the 20-hydroxyecdysone (20-E) production. This study aimed to evaluate the effect of exogenous melatonin on the growth and development, physiology, and content of 20-E in P. glomerata plants. To achieve this, P. glomerata was grown in vitro for 35 days in a culture medium supplemented with 0, 10, 100, 500, and 1000 μM melatonin. Morphophysiological parameters, antioxidant defenses, and 20-E production were subsequently assessed. Melatonin reduced pigment content, with higher concentrations (≥ 500 µM) impairing plant growth and biomass accumulation. However, melatonin also triggered antioxidant response mechanisms, leading to increased antioxidant enzymes activity and flavonoid contents, while simultaneously reducing lipid peroxidation in leaves and H2O2 accumulation in roots. Moreover, melatonin increased the levels of amino acids, proline and proteins in the roots, while also promoting the production of 20-E (at 10 µM) and increasing the contents of zeatin, ACC, and methyl jasmonate, which are important stress-related hormones. Our findings provide further insight into the role of melatonin as a regulatory molecule in plants, with its effects being concentration-dependent.
Soil heterotrophic respiration repressed by drought stress more than soil autotrophic respiration in Stipa breviflora desert steppe, China
Authors: Han Chunxue , Sun Zhiqiang , Li Haigang
Published: November 2024

Quantification of soil carbon emissions in desert steppes is a key issue in determining the carbon budget in arid regions. However, the changes in and driving mechanisms of soil respiration (Rs) and its components in response to drought in ecosystems under long-term water stress remain unclear. In this study, rain reduction by 30% and 50% experiments were conducted to simulate drought during the growing season in 2023 in the Stipa breviflora desert steppe. Total Rs and soil heterotrophic respiration (Rh) were measured, and simultaneously, the surface soil temperature and moisture were measured at 0–10 cm. Surface soil microorganisms, microbial biomass carbon, and enzymatic activity were also tested. The results showed that drought significantly decreased soil microbial biomass carbon and enzymatic activity and inhibited Rs by 21.2% and 34.1%, with Rh contributing 16.2% and 27.5%, and autotrophic respiration (Ra) contributing 5.0% and 6.6%, respectively. The inhibitory effect of drought on soil Ra only appeared at the beginning of the growing season and then disappeared with plant growth because of the drought-resistant ability of plants in the desert steppe. Rh is the primary soil carbon release process occurring in the desert steppe, approximately four times that of Ra. Soil temperature and moisture jointly regulated Rh under extreme drought conditions (rainfall reduction of 50%); however, their influence on Ra became insignificant. This study indicates that drought slowed the decomposition of soil organic carbon and had a weak effect on plant root respiration in the S. breviflora desert steppe.
Mitigating the additive bias with the ad-IAT: a pilot study
Authors: Neroni Maria Adriana
Published: November 2024

The term "additive bias" refers to the tendency of individuals to solve problems by adding elements, even when removing elements would be a more effective approach. Both anecdotal evidence and research have shown that this bias can significantly influence decision-making and problem-solving, often leading to sub-optimal solutions. In this Brief Communication, I present the results of a pilot study assessing the effectiveness of the newly developed Additive Bias Implicit Association Test (ad-IAT) as an educational tool for increasing individuals' awareness of their own biases. The findings suggest that the ad-IAT provides educational benefits comparable to those gained from direct experience with biases, which typically requires more time and conscious awareness to develop.
The Influence of Section Diameter on the Ultrasonic Fatigue Response of 316L Stainless Steel Manufactured via Laser Powder Bed Fusion
Authors: Trombley Megan , Birnbaum Andrew , Allison John
Published: November 2024

In this investigation, the influence of section diameter on high cycle fatigue (HCF) behavior of additively manufactured 316L stainless steel was characterized. Three gauge-section diameters (5.0 mm, 2.5 mm, and 1.5 mm) were examined for their influence on the ultrasonic fatigue response of samples built via laser-powder bed fusion (L-PBF). HCF was conducted under full reversed loading (\(\:R=-1\)) conditions. A total of 130 specimens were characterized in the as-built state at maximum stresses ranging from 70 to 220 MPa. A Random Fatigue Limit (RFL) model using a Maximum Likelihood Estimation (MLE) was used to quantify statistical variability and estimate an S-N curve fit. The fatigue response shows that the largest gauge diameter (5.0 mm) resulted in the lowest fatigue strength at 89.5 ± 5.6 MPa, and the smallest diameter (1.5 mm) resulted in the highest fatigue strength at 122.0 ± 32.8 MPa. The 2.5 mm diameter specimens exhibited a fatigue strength of 98.7 ± 7.0 MPa. The primary failure mechanism in all as-built specimens was surface initiated cracking from crevices in the as-built surface finish. Additional specimens with a nominal diameter of 5.0 mm were fatigue tested with the as-built surface removed via low stress surface grinding. The fatigue strength of these samples increased to 170 MPa when 75 µm of the surface was removed and 179 MPa when the surface contour was entirely removed. Residual stresses were characterized by x-ray diffraction (XRD) and show a reduced axial residual stress with reduction in gauge diameter. Additional specimens were fatigue tested after undergoing a stress relief anneal, resulting in a 51% reduction in the residual stress and a 30% improvement in fatigue strength. An in-depth analysis of the microstructure, surface roughness, defects, and fracture surface indicate that both the surface condition and residual stress are the primary factors influencing the observed diameter effects on HCF.
Construction and Analysis of China's Carbon Emission Model Based on Machine Learning
Authors: Wang Xinzi , Sun Jian , Liang Mengkun , Ren Xiaoru , Liu Xuezhi
Published: November 2024

In response to the formidable challenge of China's substantial carbon emissions, this study introduces a comprehensive research paradigm that integrates "modeling + SHAP analysis + scenario forecasting" from the perspective of machine learning. Utilizing carbon emission data spanning from 1997 to 2021, we have constructed a machine learning model and conducted an in-depth analysis of the key factors influencing carbon emissions. Based on current national policies, predictions for carbon emissions have been made. Firstly, factors affecting carbon emissions were selected in accordance with the principle of data availability. Secondly, by calculating the Spearman correlation coefficients, nine explanatory variables including the share of coal in total energy consumption and urbanization rate, had correlation coefficients of 0.6 or higher and significantly correlated with China's carbon emissions. Subsequently, the contribution of each explanatory variable in the optimal model was quantified using the SHAP method, revealing that energy intensity and urbanization rate are the key factors affecting China's carbon emissions, exerting negative and positive impacts, respectively. Finally, through policy scenario simulation, the trend of China's carbon emissions from 2022 to 2030 was predicted. The study indicates that China's carbon emissions plateau from 2022 to 2028 and peak in 2028, with an estimated carbon emission volume of approximately 9,720 million tons in 2030.
Surviving Martian Brines: Proteomic Analysis of Escherichia coli’s Adaptation to Perchlorate Stress
Authors: Kloss Lea , Doellinger Joerg , Gries Anne , Soler Elisa , Lasch Peter , Heinz Jacob
Published: November 2024

Brines, potentially formed by the deliquescence and freezing point depression of highly hygroscopic salts, such as perchlorates (ClO4-), may allow for the spatial and temporal stability of liquid water on present-day Mars. It is therefore of great interest to explore the microbial habitability of Martian brines, for which our current understanding is, however, still limited. Putative microbes growing in the perchlorate-rich Martian regolith may be harmed due to the induction of various stressors including osmotic, chaotropic, and oxidative stress. We adapted the model organism Escherichia coli to increasing sodium perchlorate concentrations and used a proteomic approach to characterize the adaptive phenotype. Separately, the microbe was adapted to elevated concentrations of sodium chloride and glycerol, which enabled us to distinguish perchlorate-specific adaptation mechanisms from those in response to osmotic, ion and water activity stress. We found that the perchlorate-specific stress-response focused on pathways alleviating damage to nucleic acids, presumably caused by increased chaotropic and/ or oxidative stress. The significant enrichments that have been found include DNA repair, RNA methylation and de novo inosine monophosphate (IMP) biosynthesis. Our study provides insights into the adaptive mechanisms necessary for microorganisms to survive under perchlorate stress, with implications for understanding the habitability of Martian brines.
Correlation of CCL3 with Ferroptosis in Intervertebral Disc Degeneration: An Insight into Prognostic Significance
Authors: Chen He , Xu Peng , Mao Leijing , Wang Yicong , Feng Zian , Wang Zhongxin , Fan Zongqing , Shen Cailiang , Xu Yuanhong
Published: November 2024

Background
Intervertebral disc degeneration (IVDD) is a prevalent and debilitating condition associated with low back pain (LBP). Despite its significant impact, effective diagnostic markers for early-stage IVDD remain elusive. Recent research has implicated ferroptosis, a newly recognized form of programmed cell death, in the pathogenesis of IVDD, particularly involving disturbances in iron homeostasis. Additionally, the CC Chemokine Ligand 3 (CCL3) has been linked to macrophage migration and the progression of IVDD, yet its precise diagnostic and prognostic utility remains uncertain.
Objective
This study aims to elucidate the underlying mechanisms of ferroptosis and the involvement of CCL3 in IVDD, with the objective of establishing their diagnostic and prognostic significance. By uncovering these mechanisms, novel biomarkers and therapeutic targets for the diagnosis and prognosis of IVDD may be identified.
Methods
Single-cell sequencing data were acquired from the TCGA database, and a range of bioinformatics methods were employed for comprehensive analysis. Furthermore, validation experiments were conducted using in vitro techniques, including the analysis of human tissue samples, co-culture assays with neutralizing antibodies, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blotting.
Results
Our findings suggest that CCL3 holds promise as a diagnostic and prognostic biomarker for IVDD. Validation experiments demonstrated that CCL3 functions via the pAMPK/AMPK pathway, thereby modulating apoptosis and impacting the progression of IVDD.
Conclusion
Our study underscores the diagnostic and prognostic potential of CCL3 in patients with IVDD. Further investigations are warranted to explore therapeutic strategies targeting CCL3, ultimately enhancing the management of IVDD.
Differential effect of nano vs. micro-sized plastics on live Chlorella sp. algae in water environment.
Authors: Chorvatova Alzbeta Marcek , Mateasik Anton , Chorvat Dusan
Published: November 2024

Environmental pollution by micro and nanoplastics (MPs) is becoming an imminent danger for the environment in the 21st century. However, the effect of the MPs of different sizes is still poorly understood. In this contribution, we compare the effect of fluorescently labelled polystyrene (PS) MPs of sizes between 20 nm and 2000 nm. Spectrally-resolved confocal microscopy and fluorescence lifetime imaging was employed to study the interaction of PS MPs with algae Chlorella sp. We observed differential effect between the smaller and the bigger-sized beads. MPs sized 20–500 nm created “corona-like” structures around algae and induced lowering of the chlorophyll fluorescence, indicating an effect on the cell photosynthesis. In addition, the 20 nm MPs induced shortening of the chlorophyll fluorescence lifetimes, pointing to the effect on the chlorophyll molecular environment. However, MPs of bigger sizes, 1000–2000 nm, rather acted as a “nucleus” for clustering of a number of neighbouring algae without affecting the chlorophyll fluorescence. Understanding the interaction of living organisms with MPs of different sizes is crucial to assess the impact of this environmental pollution on live organisms in their natural environment.
Exosome-derived miR-21-5p promotes pancreatic cancer progression via ABCD2 gene
Authors: Zhou Ming , Wang Zhixin , Zheng Li , Wang Hongli , Lin Hao , Zheng Shengbin , Lu Shiyun
Published: November 2024

Pancreatic cancer is an aggressive malignancy with a dismal prognosis, and the underlying molecular mechanisms remain only partially understood. This study aimed to clarify the role of microRNA-21-5p (miR-21-5p) in pancreatic cancer progression and to investigate the associated mechanisms. We found that miR-21-5p was significantly elevated in pancreatic cancer tissues, and its high expression correlated with poorer patients’ prognosis. Functional assays revealed that miR-21-5p enhanced the proliferation, migration, and invasive capabilities of pancreatic cancer cells. Through bioinformatics analysis and experimental validation, we discovered ATP-binding cassette transporter D2 (ABCD2) as a novel direct target gene of miR-21-5p. ABCD2 expression was significantly downregulated in pancreatic cancer tissues, and its low expression was associated with reduced patient survival. Mechanistically, miR-21-5p inhibited ABCD2 transcription and translation by directly targeting its 3'UTR, a process facilitated by exosome delivery. Importantly, overexpression of ABCD2 effectively reversed the pro-oncogenic effects of miR-21-5p. Our findings establish the critical role of the miR-21-5p/ABCD2 axis in pancreatic cancer progression and highlight the tumor-suppressive function of ABCD2. ABCD2 may represent a promising therapeutic target and a potential site for the diagnosis and treatment of pancreatic cancer.
Nighttime Fluorescence Phenotyping Reduces Environmental Variability for Photosynthetic Traits and Enables the Identification of Candidate Loci in Maize
Authors: Li Fangyi , Grzybowski Marcin , Roston Rebecca , Schnable James
Published: November 2024

High-throughput phenotyping is crucial for unraveling the genetic basis of variation in photosynthetic activity. However, the heritability of chlorophyll fluorescence parameters measured during the day is often low as a result of high levels of variation introduced by environmental fluctuations. To address these limitations, we measured fluorescence phenotypes at night, leveraging natural dark adaptation to minimize environmental noise. This significantly increased the heritability of fluorescence traits compared to daytime measurements, with the maximum quantum yield of photosystem II (Fv/Fm) showing an increase in heritability from 0.32 to 0.72. Genome-wide association studies (GWAS) conducted using three photosynthetic fluorescence traits measured at night across two growing seasons identified several significant single nucleotide polymorphisms (SNPs). Notably, two candidate genes near SNPs linked to multiple fluorescence traits, Zm00001eb271820 and Zm00001eb012130, have known roles in photosynthesis regulation. Four of the significant signal nucleotide polymorphisms identified in GWAS conducted using nighttime collected data also exhibited statistically significant associations with the same phenotypes during the day. In a majority of other cases, direction of effect was consistent but greater variance in day measured data relative to night measured data resulted in the differences not being statistically significant. These results highlight the effectiveness of phenotyping photosynthetic traits at night in reducing environmental noise and enhancing the discovery of genomic intervals related to photosynthesis. While nighttime data collection may not be applicable for all photosynthetic traits, it offers a promising avenue for advancing our understanding of the genetic variation of photosynthesis in modern crop species.
Combined pan-immune-inflammation value and signet ring cell carcinoma predict pathological complete response and prognosis to neoadjuvant chemoimmunotherapy in locally advanced gastric cancer
Authors: Ding Jianing , Sun Xiong , Li Chengguo , Shen Qian , Li Tianhao , Tao Kaixiong , Yin Yuping
Published: November 2024

Objective
To evaluate the predictive value of pan-immune-inflammatory value (PIV) and signet ring cell carcinoma (SRCC) in pathological complete response (pCR) and prognosis in patients with locally advanced gastric cancer (LAGC) receiving neoadjuvant chemoimmunotherapy(NCIT).
Methods
We retrospectively analyzed the clinicopathologic data of LAGC patients who received NCIT in the Union Hospital, Tongji Medical College of Huazhong University of Science and Technology from July 2020 to October 2023. The cut-off value of PIV was determined by receiver operating characteristic (ROC) curve analysis. Univariate analysis and multivariate logistic analysis were used to determine the correlation between clinicopathologic characteristics and pCR. Kaplan-Meier method was used for survival analysis, and log-rank test was used to compare the survival rate between groups. We performed univariate and multivariate Cox regression analyses to verify the independent prognostic factor for overall survival (OS).
Results
A total of 110 patients with LAGC were included in this study, including 86 males (78.2%) and 24 females (21.8%), with a median age of 59 years (31–74 years). SRCC and PIV were independent predictors of pCR. The Cox regression analyses showed that neutrophil-to-lymphocyte ratio, SRCC (HR = 3.699, 95%CI:1.072–12.770) and SRCC - PIV score (HR = 10.630, 95%CI:1.283–88.098) were independent prognostic factors in patients with LAGC. The SRCC - PIV score was better than PIV, NLR, and SRCC in assessing the survival outcome in patients with LAGC.
Conclusions
The combination SRCC and PIV is a significant indicator for predicting therapeutic response of LAGC after NCIT, which can help to identify high-risk groups and predict prognosis.
Correlation and Consistency Analysis between Various Indirect Portal Pressure Gradients and Actual Portal Pressure Gradient
Authors: Chen Rufeng , Liu Yaozu , Ma Li , Zhang Wen , Yu Jiaze , Yang Minjie , Luo Jianjun , Ma Jingqin , Zhou Yongjie , Yan Zhiping
Published: November 2024

Objective: To evaluate the correlation and consistency between hepatic venous pressure gradient(F-HVPG) calculated as the wedged hepatic venous pressure (WHVP) minus free hepatic venous pressure (FHVP), I-HVPG calculated as WHVP minus inferior vena cava pressure (IVCP) in the hepatic segment, and portal pressure gradient (PPG).
Methods: Data were collected from 112 patients with portal hypertension undergoing transjugular intrahepatic portosystemic shunt (TIPS) along with HVPG measurement. FHVP, IVCP, WHVP, and portal venous pressure (PVP) were collected intraoperatively. Pearson’s correlation and Bland–Altman method were used to assess correlation and consistency.
Results:A total of 112 patients were retrospectively collected. The correlation coefficient (r) velues (p < 0.001) between FHVP and IVCP, F-HVPG and I-HVPG, F-HVPG and PPG, I-HVPG and PPG were 0.835, 0.946, 0.667 and 0.698, respectively; the determination coefficient (R2) values were 0.697, 0.895, 0.445 and 0.487, respectively. Bland–Altman plots showed that F-HVPG and I-HVPG had the narrowest 95% limits of agreement. Among patients with FHVP-IVCP > 2 mmHg, the (r) vlues (p < 0.05) between F-HVPG and I-HVPG, F-HVPG and PPG,I-HVPG and PPG were 0.907, 0.648 and 0.807, respectively; the (R2) values were 0.822, 0.420 and 0.651, respectively. Bland–Altman plots showed that I-HVPG had the narrower 95% limits of agreement with PPG.
Conclusion: F-HVPG and I-HVPG demonstrated high correlation and consistency. When the difference between FHVP and IVCP is greater than 2 mmHg, IVCP should be used to calculate HVPG instead of FHVP.
Going beyond quantification: Applying a multidimensional qualitative analysis approach to support decision making for sustainable biorefinery deployment – a case study
Authors: Knoebl Melanie , Fazeni-Fraisl Karin , Lindorfer Johannes , Puschnigg Stefan , Friedl Christina , Mueller Christoph
Published: November 2024

The rollout of bio-based technologies is key to achieving sustainability goals in the bioeconomy and renewable energy sectors. Evaluating the contribution of the biorefinery value chain to sustainability goals requires the evaluation of environmental, economic, and social aspects. Most current studies use quantitative metrics focused on environmental and economic assessments, which can lead to information loss. This study adds to the current literature by presenting a comprehensive qualitative sustainability analysis for decision support, exemplified by an industrial cellulosic ethanol biorefinery value chain established in rural Romania. The study involved stakeholder, qualitative indicator (PESTEL), and SWOT analyses to derive recommendations for further biorefinery deployment and decision support. These three methods were merged with the socio- and multi-criteria model for reducing barrier analysis, a multidimensional approach that demonstrates a comprehensible way to process and interpret qualitative information. The insights gained facilitate informed decision-making, resource allocation, and policy formulation for successful biorefinery deployment. Understanding the multifaceted implications of the cellulosic ethanol biorefinery value chain facilitates the pursuit of a socially, environmentally responsible, and economically viable pathway. This paper concludes with recommendations for the maintenance and further development of lignocellulosic biorefineries in rural Romania.
Association of Body-Roundness Index and Diabetes with New-Onset Cardiovascular Disease among Middle-age and Older Adults: Evidence from the China Health and Retirement Longitudinal Study
Authors: Kong Youli , Luo Qian , Zhang Qing , Wei Quan
Published: November 2024

Background
Cardiovascular disease (CVD) is the leading cause of mortality and morbidity among non-communicable diseases. In China, diabetes is renowned for its high incidence rate, and the dody roundness index (BRI) is an emerging indicator for assessing obesity, particularly abdominal obesity. Diabetes and a high BRI may lead to new-onset CVD events, yet the relationship between diabetes, BRI, and the occurrence of new CVD incidents remains unclear.
Methods
Data for this analysis were extracted from the China Health and Retirement Longitudinal Study (CHARLS). Our research utilized a cohort that was meticulously assessed over a period from 2011 to 2018, encompassing a comprehensive follow-up of 17,708 participants. Ultimately, this study focused on a subset of 6,737 individuals who were aged 45 years or older. Methodological approaches included logistic regression, Cox regression, and mediation analysis to explore the relationships of interest. All statistical computations were meticulously executed utilizing the R programming language (version 4.2.1).
Results
Ultimately, this study encompassed 6,737 participants, all of whom were above the age of 45. Our findings revealed that within this demographic, 303 individuals (comprising 4.50%) were diabetic, while 1,481 (21.98%) experienced new-onset cardiovascular disease (CVD).The Kaplan-Meier survival analysis further delineated that the group characterized by no diabetes and low BRI (NDM.LBRI) demonstrated the lowest cumulative incidence of CVD compared to other groups. Moreover, the mediating effect of BRI on the onset of CVD among diabetic patients was particularly pronounced in the long term, exceeding four years.
Limitations
The prevalence of CVD and diabetes is self-reported, potentially introducing biases into our analysis. Furthermore, the absence of a standardized criterion for BRI categorization presents challenges. Additionally, while considering factors such as age, sex, diabetes, and BRI, our study could not account for other relevant covariates due to inevitable data gaps, which may consequently lead to an underestimation of the relationship between BRI and the co-occurrence of diabetes and new-onset CVD.
Conclusions
The findings indicate that the BRI exerts a mediating influence between diabetes and the new-onset of CVD among the middle-aged and elderly demographic in China.
Evaluation of Evapotranspiration Estimation Methods in Potato Crops: A Study on FAO-56 and Direct Measurements in the Andean Region
Authors: Estupiñan-Casallas Jhon M. , Gómez-Latorre Douglas A. , Castaño-Marín Angela María , Rodríguez-Roa Andrea O. , Góez-Vinasco Gerardo A. , Varón-Ramírez Viviana Marcela
Published: November 2024

This study evaluates and compares different methods for estimating evapotranspiration (ET) in potato crops (Solanum tuberosum L.) in the Bogotá Savannah, focusing on the FAO-56 method and direct measurements using eddy covariance (EC) systems. The research addresses the variability in crop coefficients (Kc) due to local climatic and edaphic conditions, which complicates precise ET estimation. Soil moisture was monitored throughout the crop cycle using tensiometers and volumetric moisture measurements, with an optimal water potential limit of 40 cbar. A fixed sprinkler irrigation system was employed, and soil moisture conditions were simulated using the CROPWAT 8.0 software. The study found that Method 1, which adjusts Kc values based on local conditions, provided the most accurate ET estimates, with a root mean square error (RMSE) of 0.45 mm and a Willmott’s index of agreement (d) of 0.86. The Kc values for Method 1 were 0.73, 0.87, and 0.80 for the initial, mid, and final stages, respectively. In contrast, Method 5, which uses standard FAO-56 values, showed the poorest performance. The CROPWAT simulations indicated that Method 1 also closely matched the experimental irrigation requirements, Methods 2 and 3 significantly overestimated irrigation needs, while Method 5 underestimated them in the initial stages but overestimated during maturation. These results highlight the importance of adjusting Kc values to local conditions to improve irrigation efficiency and crop health. The findings provide a robust methodology for irrigation planning and optimization, contributing to agricultural sustainability and water resource conservation.
Amide proton transfer-weighted imaging and apparent diffusion coefficient imaging with histogram analysis to predict tumor budding in rectal cancer: a preliminary study
Authors: du yunxia , he yuqi , xu wenxiang , sun yun , li feixiang , pan nini , wang lili , cai wei , Huang Gang
Published: November 2024

Objectives To investigate the value of histogram features based on amide proton transfer-weighted(APTw) imaging and apparent diffusion coefficient(ADC) images combined with clinical data and conventional magnetic resonance imaging(MRI) features in the preoperative prediction of tumor budding(TB) grade in rectal cancer (RC).
Methods We included a total of 71 TB patients who underwent surgical resection and pathological confirmation of RC between June 2023 and June 2024. The patients were classified into the low-intermediate grade group(n=44) and the high grade group (n=27) based on pathological findings. Histogram features are extracted by delineating a four-layer contour of the largest level of the tumor on APTw and ADC images. Following feature screening, the optimal histogram model is selected using machine learning, and the histogram feature score (Histogram-score) is calculated. Measurement of APTw signal intensity (SI) and ADC values was performed by subjectively delineating the region of interest (ROI) in the largest section of the tumor. Univariate logistic regression analysis was implemented to identify independent risk factors, including both clinical Characteristics, conventional MR features and Histogram-score. Subsequently, models for conventional MRI and combined model were constructed using multivariable binary logistic regression analysis for the purpose of predicting TB grade. Then, we plotted combined model into a nomograh for personalized prediction. Evaluation of model performance and clinical practicality was conducted using area under curve (AUC), calibration curve, and decision curve.
Results APTw SI was significantly higher in the high group compared with the low-intermediate grade group (P < 0.05). The value of ADC was significantly lower in the high group compared with the low-intermediate group (P < 0.05). The AUC of the conventional MRI model constructed on the basis of MRI-T stage, APT SI and ADC value was 0.891 (95% CI: 0.795, 0.953). A histogram model was composed of 5 histogram features filtered from the optimal SVM machine learning algorithm with AUC of 0.939 (95% CI: 0.856, 0.982). The AUC of the combined model constructed using ADC value and Histogram-score was 0.960 (95% CI: 0.885, 0.992). The combined model had higher diagnostic efficacy than the histogram model (P = 0.14) and the conventional MRI model (P = 0.04).
Conclusions The combined model constructed on the basis of histogram features of APTw and ADC images and conventional MRI features can effectively predict the TB grade of RC patients preoperatively, providing a preoperative noninvasive assessment method for the selection of treatment options and prognostic evaluation of RC patients.
3D Finite Element Analysis of Hybrid Prostheses on Pterygoid Implants of Varying Lengths in Edentulous Maxilla
Authors: AKBULUT Kuddusi , Caglar Alper
Published: November 2024

OBJECTIVE
The aim of this study is to evaluate the effects of titanium framework hybrid prostheses designed for pterygoid implants of varying lengths in completely edentulous patients.
BACKGROUND
In cases of complete edentulism, insufficient bone volume and quality significantly increase the risk of complications during implant surgery. This is particularly challenging in the posterior maxilla, where severe atrophy complicates the placement of dental implants. Pterygoid implants are proposed as an alternative solution to address these challenges.
METHODS
This study was conducted at the Faculty of Dentistry, Yıldırım Beyazıt University. Hybrid prostheses were designed using Nobel Branemark implants, and stress distributions on the implants and surrounding bone were evaluated through three-dimensional finite element analysis (FEA). The implants were categorized into two groups based on their placement in the anterior and posterior regions, with specific angles and lengths detailed in the methodology.
RESULTS
The findings indicated that the highest Von Mises stress values were concentrated at the neck region of the implants. Maximum and minimum principal stresses were observed in the peri-implant area. An increase in implant length altered the stress distribution within the implants but did not significantly affect the surrounding bone stress levels.
Short-distance seed and pollen dispersal in both hunted and intact forests in the lower canopy African rainforest tree, Coula edulis Baill (Coulaceae)
Authors: Kamdem Narcisse Guy , Sonké Bonaventure , Sergeant Saskia , Deblauwe Vincent , Hardy Olivier J.
Published: November 2024

Background
Mammal-dispersed tropical trees can face regeneration problems due to increasing hunting pressure. We studied the case of Coula edulis Baill (Coulaceae), an African rainforest tree that produces the 'African walnut', an essential food and income resource for rural communities in Cameroon. We compared gene flow and regeneration dynamics in three populations with contrasting levels of human disturbance and mammal abundance. Using 21 nuclear microsatellite markers, we estimated the outcrossing rate and contemporary seed and pollen dispersal distances, and we analyzed the fine-scale spatial genetic structure (FSGS) to infer historical gene dispersal distances.
Results
Juveniles were outcrossed while 22–30% of the seeds were selfed, suggesting the elimination of inbred seeds. The mean dispersal distances were relatively short for seeds (105–219 m) and pollen (173–358 m), both shorter in the most intact forest. Immigration rates were three to four times higher for pollen (33–71%) than for seeds (7–28%), indicating some long-distance pollen dispersal. FSGS was strong in all populations (Sp = 0.023–0.036), suggesting short-range historical gene dispersal distances consistent with contemporary estimates. We detected assortative mating, possibly due to higher flowering synchronicity between related individuals. The most disturbed plots had an inverted J-shaped trunk diameter structure, typical of continuous regeneration, while the intact forest had a complex diameter structure with a weak regeneration pulse.
Conclusions
Our results suggest that forest disturbance and mammal hunting do not significantly affect the dispersal distances of seed and pollen for Coula edulis, contrary to other mammals-dispersed trees. We hypothesize that the main dispersers are scatter hoarding rodents that are less impacted, or even facilitated, by hunting pressure. The species appears to regenerate better in disturbed forests, possibly due to a reduction in seed and seedling predators. However, natural populations are threatened by ongoing forest conversion into agriculture.