bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptomics-based Mining and Analysis of Low Nitrogen Tolerance Related Genes in Foxtail Millet
Authors: Qin Na , Fu Senjie , Zhu Cancan , Dai Shutao , Song Yinghui , Jing Ya , Ye Zhenyan , Wang Chunyi , Li Junxia
Published: February 2024

Background: Nitrogen (N) is a nutrient element crucial for the growth and development of crops. A better understanding of the effects of low-N stress on millet (Setaria italica L.) production, a model crop for studying low-N tolerance, and the underlying molecular mechanisms responsible for low-N stress responses is vital to improvement of agricultural production.
Results: In this study, we used RILs as materials, its parental lines ‘Yugu 28,’ a low N-tolerant millet variety, and ‘Qiye Huang,’ a low N-sensitive variety. A transcriptomic study using leaves collected twenty-one days after normal and low-N treatment, the N concentration was 2.5 and 0.5 mmol·L-1, respectively. In total, 894 differentially expressed genes (DEGs) were identified between normal and low-N treatment. Further analysis revealed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to amino acid, carbon, N, and lipid metabolism and secondary metabolite biosynthesis. Co-regulation analysis suggested that 15 DEGs contributed to the formation of a regulatory network involving multiple biological processes and pathways including nitrogen or amino acid biosynthesis, uptake, metabolism and utilization. RNA-seq analysis also showed that some nitrogen metabolism-related DEGs were highly expressed in low-N stress compared to normal N conditions. The changes in expression of low N-responsive genes determined by RNA sequencing were confirmed by reverse-transcription PCR for nine genes.
Conclusions:The transcriptome is beneficial for identified the candidate genes of millet in response to low nitrogen stress, SiGS1 (LOC101764285) and SiNPR2 ((LOC101764285)) were identified as potential candidate genes for improving low nitrogen stress tolerance. These results are a first step to understanding the molecular mechanisms of low-N tolerance in foxtail millet and lay a foundation for its genetic improvement.
Baseline tebuconazole sensitivity and potential resistant mechanisms in Fusarium graminearum
Authors: Zhou Feng , Zhou Xiaoli , jiao Yan , Han Aohui , Zhou Huanhuan , Chen Zeyuan , Li Wei Guo , Liu Runqiang
Published: February 2024

Background
The Fusarium head blight caused by Fusarium graminearum results in reduced crop yields and the potential for vomitoxin contamination, which poses a risk to both human and livestock health. The primary method of control relies on the application of chemical fungicides.
Results
The current study found that the tebuconazole sensitivity of 165 F. graminearum isolates collected from the Huang-Huai-Hai region of China between 2019 and 2023 ranged from 0.005 to 2.029 µg/mL, with an average EC50 value of 0.33 ± 0.03 µg/mL. The frequency distribution conformed to a unimodal curve around the mean, and therefore provides a useful reference for monitoring the emergence of tebuconazole resistance in field populations of F. graminearum. Analysis of five tebuconazole-resistant mutants produced under laboratory conditions indicated that although the mycelial growth of the mutants were significantly (p < 0.05) reduced, spore production and germination rates could be significantly (p < 0.05) increased. However, pathogenicity tests confirmed a severe fitness cost associated with tebuconazole resistance, as all of the mutants completely loss the ability to infect host tissue. Furthermore, in general the resistant mutants were found to have increased sensitivity to abiotic stress, such as ionic and osmotic stress, though not to Congo red and oxidative stress, to which they were more tolerant. No cross-resistance was detected between tebuconazole and other unrelated fungicides such as flutriafol, propiconazole and fluazinam, but there was a clear negative cross-resistance with triazole fungicides including fludioxonil, epoxiconazole, metconazole, and hexaconazole. Meanwhile, molecular analysis identified several point mutations in the CYP51 genes of the mutants, which resulted in two substitutions (I281T, and T314A) in the predicted sequence of the FgCYP51A subunit, as well as seven (S195F, Q332V, V333L, L334G, M399T, E507G, and E267G) in the FgCYP51C subunit. In addition, it was also noted that the expression of the CYP51 genes in one of the mutants, which lacked point mutations, was significantly up-regulated in response to tebuconazole treatment.
Conclusions
These results provide useful data that allow for more rational use of tebuconazole in the control of F. graminearum, as well as for more effective monitoring of fungicide resistance in the field.
Can We Raise a Sternochondral Joint Flap Based on Internal Thoracic Vessels for Temporomandibular Joint Reconstruction? A Preliminary Cadaveric Study
Authors: Alpat Servet Elçin , Aydın Mehmet , Kaya Burak , Açar Halil İbrahim
Published: February 2024

Purpose The free fibula flap is the gold standard for reconstructing mandibular defects caused by trauma, tumors, dysplastic diseases, osteoradionecrosis, and atrophy, but it has not yet been shown to be the ideal method for condylar reconstruction. This anatomical study proposes a surgically pragmatic approach to temporomandibular joint and condylar reconstruction via defining sternochondral joint vascularity.Methods Six fixed cadavers were dissected to assess the suitability of the 4th rib for the planned procedure. The internal thoracic vessels and branches near the sternochondral joint were carefully identified. The sternochondral joint flap was then harvested, focusing on cartilaginous rib to preserve the joint surface and vascular network. After contouring to fit the temporomandibular joint and condylar deformity, the flap was securely placed. Additional pedicle length measurements were taken.Results Perforators of the internal thoracic artery and vein constituted the dominant pedicle. The mean pedicle length was sufficient to reach recipient vessels on the neck. The compatibility between the 4th sternochondral flap and the glenoid fossa was confirmed.Conclusion A multitude of therapeutic approaches have been employed in the past to reconstruct the temporomandibular joint and condyle, albeit with restricted efficacy owing to chondral graft resorption or size mismatch in three-dimension. In contrast, this study shows that the fourth sternochondral joint flap is a promising free flap with ideal pedicle positioning, length, and vascular size match at the anastomosis. This technique is suitable for reconstructing this inherently difficult region of the temporomandibular joint, thereby offering reconstructive surgeons another method in their armamentarium.
An Experimental Comparative Performance Study of Variable Area Ejectors in Different Operating Conditions
Authors: Kumar Virendra , Subbarao P M V
Published: February 2024

This research experimentally compares the performance of two variable area ejectors designed based on the Constant Rate of Momentum Change (CRMC) approach and the Constant Rate of Kinetic Energy Change (CRKEC) approach. Ejector systems were designed for specific design and operating conditions to perform experiments. The pressure recovery ratio (PRR) and entrainment ratio (ω) at on-design operating conditions were compared using the experimental results. The study also optimized the entrainment ratio of both systems at off-design conditions. The results indicate that both variable-area ejectors based on CRMC and CRKEC have their own advantages and limitations in terms of performance and suitability for specific applications. CRMC ejectors provide higher entrainment ratios (0.512) and lower pressure recovery ratios (0.178), while CRKEC ejectors provide slightly higher pressure recovery ratios (0.18) and lower entrainment ratios (0.5) at on-design conditions. Furthermore, the study investigated the off-design impact of nozzle exit positions (NXPs) and the pressure of motive and secondary flows on the entrainment ratio of both ejectors.
Bridging the Gap: Exploring the Causal Relationship between Metformin and Tumors
Authors: zhang zexin , wu wenfeng , wu zexia , he yihan , chang xuesong , deng shenyuan , zhou rui , chen yadong , zhang haibo
Published: February 2024

Objective
Many studies have reported that metformin can reduce the risk of tumor. However, the level of evidence is low, and the results of the studies are conflicting.
Methods
We conducted a tumor associated Phenome-wide Mendelian randomization (MR-PheWAS) analysis to explore the causal relationship between metformin and tumors. Two cohorts of metformin came from UK Biobank. The full phenotype data of tumors came from FinnGen_R10. We elucidated the causal association through two-sample MR analysis (TSMR). More importantly, we conducted a meta-analysis to ensure the unbiased results. In MR analysis, we used Inverse-Variance Weighted (IVW) method as the main outcome indicator. Subsequently, we integrated 2 cohorts for the meta-analysis. Finally, we attempted to explore this mechanisms through a mediational MR analysis.
Results
MR results showed that metformin may have a causal relationship with a total of 13 tumor associated phenotypes in training cohort. 4 phenotypes were validated in the testing cohort. In training and testing cohort, metformin have a protective effect on Malignant neoplasm of breast, HER-positive, Brain meningioma, Malignant neoplasm of oral cavity and Malignant cancer of tonsil and base of tongue. Intriguingly, after integrating the results of two cohorts for meta-analysis, a total of 12 results were significant. A mediational MR analysis showed that the effects of metformin against Brain meningioma may be weaken by family Oxalobacteraceae.
Conclusions
Metformin may have potential preventive and therapeutic effects on a variety of tumors, we don’t recommend routine use of metformin alone because there was no clear cause-and-effect relationship between them.
Investigate an optimal extracorporeal shock wave therapy intervention strategy for osteonecrosis of femoral head : a retrospective analysis
Authors: Zhu JunYu , Xiao jian , Li Hao , Xing Gengyan , Yan Jun
Published: February 2024

Purpose: To investigate an optimal ESWT intervention strategy in the management of ONFH.
Methods: An analysis of medical records was performed retrospectively on 75 patients who received extracorporeal shock wave therapy(ESWT) between June 2021 and July 2023, all patients affected by ONFH. These patients underwent MRI before treatment, 3 months, and 1 year after treatment to measure their volume; their Harris and VAS were recorded at the corresponding time points. Correlation analysis and regression analysis were performed to examine the correlation between necrotic volume and Harris, VAS before treatment and the correlation between the change of necrotic volume size and the evolution of HHS 1 year after treatment.
Results:A statistically significant correlation between the size of the necrotic volume and the Harris and VAS was demonstrated before treatment(P＜0.001). Three months after treatment, there were significant improvements in Harris and VAS(P＜0.001) but unchanged in MRI images. One year after treatment, the Harris, VAS, and size of necrotic volume from 13 patients were significantly improved(P＜0.001), and Linear regression analysis indicated a significant positive correlation between the size of the necrotic volume and clinical improvement(P＜0.001).
Conclusion: The volume of osteonecrosis of the femoral head was negatively correlated with Harris and positively correlated with VAS. The reduction of necrotic volume was related to clinical improvement. It shows that the degree of pain is one of the critical references to reflect the size of necrosis and physiotherapists can choose interval between two cycles according to their own changes in pain conditions.
Investigation of the etched behavior of a rose gold target by magnetron sputtering
Authors: Yuan Junping , Chen Lingxia , Pan Chengqiang , Huang Yuheng , Zhou Xiang , Lin Shanwei , Zhu Jiayi
Published: February 2024

Compared to the electroplating process, magnetron sputtering offers significant environmental advantages and has emerged as a crucial focus for research and development in jewelry surface coating. In this paper, Au85 rose gold was used to create a plane sputtering target, and the surface etched behavior of the target was studied. The experimental results indicate that the glow and sputtering process remain stable when the target current and power density are low. The target particles will sputter out layer by layer along a crystal face, forming stepped straight stripes. V-shaped grooves are formed on the target surface, and the angle between the slope of the etched area and the normal direction of the target surface is approximately 76°. With the increase in target current and power density, arc discharge occasionally during sputtering, leading to the formation of mastoid-like micromorphology on the surface of the etched area. When the current to the target is further increased, the target material melts quickly. The magnetic field configuration of the target base results in an end effect, leading to uneven depth and width of the etched groove. In order to enhance the utilization rate of the precious metal planar target, the magnetic field layout should be optimized and the power density should be kept within the threshold for arc discharge.
Is private insurance enough to address barriers to accessing dental care? Findings from a Canadian population-based study
Authors: Abdelrehim Mona , Singhal Sonica
Published: February 2024

Background
In Canada, as in many other countries, insurance plays a crucial role in facilitating access to dental care. Private dental insurance, though it greatly reduces financial barriers to dental care, does not guarantee affordability, as there are issues with the quality and level of coverage of insurance plans. Individuals experiencing barriers to dental care are expected to have poorer oral health. It is important to examine access to dental care and the oral health status of individuals with private insurance.
Methods
Our study is a secondary data analysis of the most recent available cycle (2017-18) of the Canadian Community Health Survey (CCHS), a national cross-sectional survey. Univariate analysis was conducted to determine the characteristics of Ontarians with private insurance (n = 17,678 representing 6919,814 Ontarians)—bivariate analysis to explore their financial barriers to dental care, and how they perceive their oral health. Additionally, logistic regressions were conducted to identify relationships between covariates and each outcome variable in our study (cost barriers to dental care, visiting the dentist only for emergency, perceived their oral health as “fair to poor” and “dissatisfied and very dissatisfied” with their teeth/denture appearance).
Results
We found that the majority of those with private insurance did not experience cost barriers to dental care and perceived their oral health as good to excellent. However, specific populations, including those aged 20–39 years, and those earning less than $40,000, despite having private dental insurance, faced significantly more cost barriers to access to care. Additionally, those with the lowest income (earning less than $20,000) perceived their oral health as “fair to poor” more than their counterparts. Adjusted estimates revealed that respondents aged 20–39 were six times more likely to report cost barriers to dental care and ten times more likely to visit the dentist only for emergencies than those aged 12–19. Additionally, those aged 40–59 were two times more likely to report poorer oral health status compared to those aged 12–19.
Conclusion
Given the upcoming implementation of the Canadian Dental Care Plan, the results of this study have implications for identifying vulnerable populations who currently are ineligible for insurance coverage.
Neuroinflammation Protective Efficacy of Montelukast in a Mouse Model of Parkinson’s Disease Revealed by [18F]GSK1482160 PET Quantification Targeting P2X7R
Authors: Ye Peizhen , Bi Lei , Qiu Yifan , Yang Min , Huang Guolong , Zhao Xianxian , Liu Yongshan , Hou Yuyi , Sun Rui , Zheng Pengcheng , Tong Henry Hoi Yee , Jin Hongjun
Published: February 2024

Purpose
In vivo neuroinflammation was quantified via [18F]GSK1482160 positron emission tomography (PET) imaging targeting P2X7 receptor (P2X7R) to evaluate the therapeutic effect of Montelukast (MK) treatment in transgenic A53T mice model of Parkinson's disease (PD).
Methods
MK treatment (10 mg/kg, i.g.) was performed in a mice model of PD for 5 weeks. Movement disorder was measured by motor functional tests (grip tests, pole tests, and inverted screen tests), the expression of microglial P2X7R was quantified by [18F]GSK1482160 positron emission tomography-Magnetic Resonance Imaging (PET-MRI) as well as ex vivo autoradiography, and the damage of dopaminergic neurons (DA neurons) was quantified by [18F]L-DOPA PET-MRI in PD mice to monitor the therapeutic effect of MK. The movement abnormality was exploited by performing a correlation analysis between the PET quantification and motor functions. Immunofluorescence staining was performed to validate the results of PET-MRI.
Results
PD mice suffered from severe motor deficits accompanied by increased neuroinflammation throughout the brain regions, as well as partially damaged DA neurons in striatum. The MK treatment significantly improved the motor deficits (grip test: PD + NS: 0.630 ± 0.020 N vs. PD + MK: 0.736 ± 0.011 N, p < 0.0001). PET measurement indicated that MK treatment significantly reduced the brain uptakes of [18F]GSK1482160 (SUVRLV in striatum: PD + NS: 1.701 ± 0.047 vs. PD + MK: 1.313 ± 0.075, p < 0.0001). Correlation analyses showed that motor function was positively correlated with [18F]L-DOPA PET in stratum (p = 0.0482, r = 0.5565), and was negatively correlated with [18F]GSK1482160 PET in brain globally (p = 0.0008, r = -0.7342).
Conclusions
[18F]GSK1482160 is a promising PET tracer for assessing neuroinflammation in PD. In vivo monitoring of inflammation in PD is beneficial to explore the association between movement disorders and the neurological damage in the brain regions, and to detect potential damage to non-DA neurons, which facilitates the assessment of the disease and contributes to the early diagnosis and treatment of PD.
High Prevalence of Work-Related Musculoskeletal Disorders Among Gastrointestinal Endoscopy Nurses in China: A Cross-Sectional Survey Study
Authors: WANG Maosha , Li Wen , Wang Jing , CHEN Ting , Liu Feng , ZHANG ying
Published: February 2024

Background and objectives:
Gastrointestinal endoscopy has assumed a paramount role in modern gastroenterology, characterized by notable advancements in techniques. Consequently, considerable attention has been directed towards investigating the prevalence of work-related musculoskeletal disorders among gastrointestinal endoscopists. However, an equally important aspect that warrants investigation is the prevalence of WMSD experienced by gastrointestinal endoscopy nurses, who play a vital role in the procedure. While previous studies in the United States have reported varying rates of WMSD (ranging from 19.6% to 52.2%) among these nurses, the data pertaining to the Chinese gastrointestinal endoscopy nurse population is notably lacking. Hence, this study endeavors to assess the prevalence, affected sites, prevalence rate, and potential risk factors of WMSD among Chinese gastrointestinal endoscopy nurses.
Methods:
To achieve this objective, an anonymous electronic survey comprising 62 questions was administered to 528 gastrointestinal endoscopy nurses.
Results:
The survey was completed by 396 respondents, revealing that 376 nurses (94.9%) reported experiencing WMSD in at least one location. The most frequently reported pain symptoms encompassed low back pain (reported by 316 nurses, 79.8%), neck pain (reported by 311 nurses, 78.5%), and shoulder pain (reported by 296 nurses, 74.7%). Notably, through multivariate logistic regression analysis, the study identified frequent forward/backward neck tilting at work and a confined workspace as significant associated risk factors for shoulder WMSD, while frequent pushing and pulling of heavy objects and a tight workspace emerged as significant risk factors for low back WMSD.
Conclusions:
In conclusion, the study found that WMSD is highly prevalent among registered nurses engaged in gastrointestinal endoscopy care, with the lower back, neck, and shoulder being the most commonly affected areas. To address this issue effectively, it is imperative to focus on understanding the occurrence and mechanisms underlying WMSD, imparting preventive knowledge, and implementing ergonomic protective measures. Incorporating these aspects into the professional training of gastrointestinal endoscopy nurses is of paramount importance.
A Novel Approach to Detect Driver Drowsiness Using Transfer Learning and Hybrid Features
Authors: S Priyanka , S Shanthi
Published: February 2024

In worldwide, drowsiness is one of the prevalent reasons to cause accident. Statistics show that fatigued drivers are a major factor in causing many accidents. According to studies by the National Sleep Foundation, 20% of drivers feel sleepy to some extent while driving. Deep learning-based methods are the most recent ones that researchers have used to analyse videos and detect tiredness. Convolution neural networks utilizes extracted face features like yawning, eye flashing and head movements to detect exhaustion and sleepiness. Incorporating modified InceptionV3, VGG16, ResNet50, DenseNet201 and MobileNetV2 architecture over Driver Drowsiness Dataset to propose an ensemble deep learning model. Feature extraction was done using these models. The global max pooling layer is used to improve spatial robustness and dropout approach was included in these models to avoid overfitting on training data. Finally, Sigmoid classifier is used to classify positive (drowsy) or a negative (nondrowsy) result. These models outputs are given to a proposed ensemble algorithm. This model outperforms the alternative strategy with respect to performance metrics. The suggested ensemble framework performs better in identifying driver drowsiness than existing state-of-the-art techniques on basis of accuracy.
Unveiling Pandemic Patterns: A Detailed Analysis of Transmissibility and Severity Parameters Across Four COVID-19 Waves in Bogotá, Colombia
Authors: Cucunuba Zulma , Quevedo David Santiago , Domigues Nicolas , Perez Diego , Cabrera Maria Alejandra , Serrano Juan David , Abril Felipe Segundo , Moyano Diane , Rios Diana Sofía , Gonzalez Manuel , Whittaker Charles
Published: February 2024

This retrospective study on COVID-19's four waves in Bogotá, Colombia, scrutinises 1.77 million cases from March 2020 to April 2022, revealing significant shifts in both transmissibility and severity. The study highlights dynamic changes in the instantaneous reproduction number (Rt), with the highest values (> 2.5) corresponding to the ancestral and Omicron variants. There was a notable 88% decrease in the Case Fatality Ratio (CFR) from the first to the fourth wave, emphasising changing severity levels. The third wave, marked by the Mu variant, saw the highest case and death counts, yet paradoxically showed a decrease in CFR and an increase in the hospitalisation fatality ratio. Conversely, the fourth wave, dominated by Omicron, had the lowest severity despite higher hospitalisation rates in children. Additionally, the study records a consistent reduction in average hospital and ICU stay durations, from 10.84 days to 7.85 days and from 16.2 days to 12.4 days respectively, across the waves. These findings underscore the importance of ongoing epidemiological surveillance and adaptable public health strategies in lower-middle-income regions like Bogotá, deepening our understanding of COVID-19's impact in Latin America.
Novel stochastic multi breather type, a-periodic, hybrid periodic and other type of waves of the Shrödinger-Hirota model with Wiener process
Authors: AL-Essa Laila A. , Rahman Mati ur
Published: February 2024

The current manuscript elaborate a novel characteristic of stochastic multi breather type, periodic, hybrid periodic and different type of waves solutions for the Shrödinger-Hirota (SH) equation. The mentioned equation is studied by a Wiener process and white noise which is used for the sudden and large-scale fluctuation. By applying the wave transformation technique the considered equation is transformed into ordinary differential equations, gives meaningful analysis. From the solution of the SH equation various type of results, including soliton, dark, bright, hybrid and periodic solitons. To visually capture these intricate behaviors, we employ MATLAB tools to generate 2D and 3D graphs of the analytical stochastic solutions. This combination of mathematical rigor and numerical simulations provides a comprehensive understanding of the phenomena under study, making a valuable contribution to the field of nonlinear wave equations and stochastic processes.
Harnessing the optimization of enzyme catalytic rates in engineering of metabolic phenotypes
Authors: Razaghi-Moghadam Zahra , Babadi Fayaz Soleymani , Nikoloski Zoran
Published: February 2024

The increasing availability of enzyme turnover number measurements from experiments and of turnover number predictions from deep learning models prompts the use of these enzyme parameters in precise metabolic engineering. Yet, there is no computational approach that allows the prediction of metabolic engineering strategies that rely on modification of turnover numbers. It is also unclear if modifications of turnover numbers without alterations in the host’s regulatory machinery suffice to increase the production of chemicals of interest. Here, we present a constraint-based modelling approach, overcoming kinetic obstacles (OKO), that uses enzyme-constrained metabolic models to predict in silico strategies to increase the production of a given chemical, while ensuring specified cell growth. We demonstrate that the application of OKO to enzyme-constrained metabolic models of Escherichia coli and Saccharomyces cerevisiae results in strategies that can at least double the production of over 40 compounds with little penalty to growth. Interestingly, we show that the overproduction of compounds of interest does not entail only an increase in the values of turnover numbers. Lastly, we demonstrate that a refinement of OKO, allowing also for manipulation of enzyme abundance, facilitates the usage of the available compendia of turnover numbers in the design of precise metabolic engineering strategies.
Construction of a five-disulfidptosis-related-lncRNA signature for predicting prognosis and immune activity in kidney renal clear cell carcinoma
Authors: Xu Kangjie , Li Dongling , Liu Hui , Qian Jinke , Ji Kangkang , Zhang Yanhua , Zhang Minglei , Zhou Hai , Hou Xuefeng , Jiang Jian , Zhang Zihang , Mao Weipu , Dai Hua , Li Li
Published: February 2024

Background: Kidney renal clear cell carcinoma (KIRC) is a highly aggressive cancer. Disulfidptosis is a novel mechanism of programmed cell death. However, the role of disulfidptosis-related lncRNAs (DRlncRNAs) in KIRC remains unknown. This study aimed to develop a prognostic model based on DRlncRNAs and examine their prognostic value in KIRC.
Methods: RNA sequencing and relevant clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses and the lasso algorithm were used to identify prognostic DRlncRNAs and establish a prognostic model. Multiple methods were used to assess the reliability of the model. Gene set enrichment analysis (GSEA), immune infiltration analysis and somatic mutation analysis were performed to evaluate the predictive performance of the model, and anticancer drugs were predicted.
Results: The prognostic model was established based on five DRlncRNAs and was identified as a good predictor of the survival and prognosis of patients with KIRC. GSEA revealed that DRlncRNAs were associated with apoptosis and immune-related pathways. Immune analysis suggested that low-risk patients had better immunotherapeutic outcomes. Somatic mutation analysis revealed that low-risk patients had a lower somatic mutation rate and TMB score and a better prognosis. In addition, axitinib, ibrutinib, osimertinib and ruxolitinib were found to be more effective in low-risk patients, whereas crizotinib, lapatinib, linsitinib and nilotinib were found to be more effective in high-risk patients. Finally, qRT-PCR was performed to determine the expression of DRlncRNAs in normal kidney cells and KIRC cell lines.
Conclusion: We constructed a risk model and proposed a novel strategy for diagnosing and treating KIRC.
Linking Sustainability Reporting and Energy Consumption Through Global Reporting Initiative Standards and Sustainable Development Goals
Authors: Molnár Péter , Tóth Árpád , Lukács Bence
Published: February 2024

In response to the urgent need for a comprehensive approach to reporting that integrates real business impacts and sustainability dimensions, this study introduces a novel methodology. Building on the synergy between Global Reporting Initiative (GRI) standards, Sustainable Development Goals (SDG) targets and environmental, social, and governance (ESG) considerations, the theoretical framework provides a structured methodology for organizations to articulate their contributions to global sustainability goals. By linking the analysis of GRI standards to the Affordable and Clean Energy SDG, this approach not only analyses reporting processes but also lays the groundwork for advanced analytics by linking corporate environmental impact and sustainability reporting. Empirical findings from a homogeneous sample of companies highlight the need to improve the accuracy, efficiency, and relevance of reporting. In addition, the study underscores the broader societal benefits of sustainability reporting practices, enhancing stakeholder trust, and enabling more informed decision-making. As such, this research advances the discourse on sustainable practices and reporting, provides practical implications for practitioners, and contributes to a more sustainable future.
Molecular Docking Simulation of Antidiabetic Molecules of Libas (Spondias pinnata) Fruit and Prediction of their Pharmacokinetic Properties
Authors: Diacos Joy Elaine
Published: February 2024

Diabetes mellitus is one of the chronic metabolic disorders which affects more than 16 million Filipinos. Proper education, medical intervention, and a good lifestyle can help control and manage this disease. Spondias pinnata is one of underutilized crops in the Philippines which is well-known for its satisfactory flavor and medicinal properties including its antidiabetic activity. A quest for natural and effective drug to manage diseases is a continuous work in progress. Drug discovery and design is a tedious and expensive process. Computer-aided drug design guides the design and makes the process more efficient and less costly. Molecular docking simulation was used to determine the potential antidiabetic compounds from the 48 reported compounds found in S. pinnata fruit. Seven compounds namely squalene (-9.1kcal/mol), rutin (-9kcal/mol), catechin(-8.7kcal/mol), quercetin (-8.5kcal/mol), tocopherol (-8.4kcal/mol), myricetin (-8.4kcal/mol), and ellagic acid (-8.3kcal/mol) showed comparable binding affinity with peroxisome proliferator-activated receptor gamma (PPARγ). Tocopherol and catechin showed good ADMET properties. Between the two compounds, catechin passed the four filters for drug-likeness. Thus, catechin can be a potential compound that can be used to develop antidiabetic drugs.
The Hazards of Fine Particulate Matter on Mice Kidney: Effects from Different Emission Sources and Potential Toxic Components
Authors: Cheng Fu-Jen , Chang-Chien Guo-Ping , Chen Pei-Shih , Tseng Yu-Lun , Yuan Chung-Shin , Lai Ching-Shu
Published: February 2024

Associations exist between fine particulate matter (PM2.5) exposure and impaired kidney function. However, the specific mechanisms and components causing renal damage remain unclear. PM2.5 was collected from an industrial and a rural area. Mice were categorized according to exposure, and biochemical, western blotting, histological, and immunohistochemical analyses were performed to evaluate the impact of PM2.5 constituents on their kidneys. The impact of different PM2.5 components on inflammatory responses was assessed by exposing the murine macrophage cell line (RAW 264.7); a chelating resin, which removed heavy metals from the water extract, allowed for evaluating the inflammatory effects caused by various PM2.5 constituents. The major metallic elements at the industrial site were Fe, Mg, Zn, and Ca, whereas those at site Rural were Ca, K, and Mg. PM2.5 water extracts from both sites induced inflammatory cytokine upregulation in the lungs and kidneys, and inflammatory cell infiltration, antioxidant activity downregulation, and elevated levels of kidney injury molecule 1 in the kidneys. Compared to industrial-site PM2.5, rural-site PM2.5 significantly upregulated inflammatory cytokine infiltration in the lungs, increased inflammatory cell levels in the kidneys, and significantly increased kidney Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL)-positive apoptotic cells. Exposure to PM2.5 water extract increased the mRNA levels of tumor necrosis factor-α and interleukin-6, and nitrite production in RAW264.7 macrophages. The inflammatory response and nitrite production induced by the industrial-site PM2.5 water extract were significantly suppressed after treatment with a chelating resin, whereas that in the rural area were suppressed by the Toll-like receptor 4 (TLR4) antagonist. At equivalent dosages, renal toxicity induced by the rural-site PM2.5 water-soluble components might exceed that from industrial areas. Metal components may be crucial factors in PM2.5-induced cellular inflammatory responses in industrial areas, while TLR4-mediated inflammatory pathways were a major factor responsible for this response in the rural area.
The Triple Attention Transformer: Advancing Contextual Coherence in Transformer Models
Authors: Ghaith Shadi
Published: February 2024

This paper introduces the Triple Attention Transformer (TAT), a transformative approach in transformer models, tailored for enhancing long-term contextual coherence in dialogue systems. TAT innovates by representing dialogues as chunks of sequences, coupled with a triple attention mechanism. This novel architecture enables TAT to effectively manage extended sequences, addressing the coherence challenges inherent in traditional transformer models. Empirical evaluations using the Schema-Guided Dialogue Dataset from DSTC8 demonstrate TAT's enhanced performance, with significant improvements in Character Error Rate, Word Error Rate, and BLEU score. Importantly, TAT excels in generating coherent, extended dialogues, showcasing its advanced contextual comprehension. The integration of Conv1D networks, dual-level positional encoding, and decayed attention weighting are pivotal to TAT's robust context management. The paper also highlights the BERT variant of TAT, which leverages pre-trained language models to further enrich dialogue understanding and generation capabilities. Future developments include refining attention mechanisms, improving role distinction, and architectural optimizations. TAT's applicability extends to various complex NLP tasks, affirming its potential as a pioneering advancement in natural language processing.
Can sleep hygiene interventions affect strength and power outcomes for female athletes?
Authors: Gooderick Julie , Hayes Mark , Maxwell Neil , Clash Russ , Wood Toby , Abbott Will
Published: February 2024

Background: Previous evidence has demonstrated greater sleep to enhance sprint, endurance, and sports-specific skills, however, it is yet to be investigated whether improved sleep indices could enhance strength and power performance. Sleep hygiene (SH) is growing in popularity as a tool to enhance sleep indices amongst athletic cohorts, yet the optimal delivery strategy of sleep hygiene education is yet to be determined.
Aims: The aims of this study were to investigate whether sleep hygiene interventions affect strength and power outcomes, with a secondary aim to assess whether there are any differences between individualised and group-based SH education on sleep indices in female athletes.
Methods: Using a randomised, controlled design with repeated measures, 34 female footballers were split into 3 groups: one receiving both group-based and individualised sleep hygiene, one receiving only group-based SH and a control group receiving no education. Monitoring of sleep and physical performance was carried out at week 1, 4 and 7. Split-plot ANOVAs assessed for differences between groups x weeks, and groups x time.
Results: Individualised sleep hygiene education resulted in significantly improved sleep duration (p =0.005), latency (p=0.006) and efficiency (p=0.004) at week 7 compared to controls, whilst also resulting in significantly improved countermovement jump scores (p=0.001) compared to control.
Conclusions: Participants receiving group-based sleep hygiene education only, demonstrated significantly improved sleep efficiency compared to controls (p=0.032). Jump performance may be affected by sleep factors, and individualised SH may be superior to group-based SH. This provides information to coaches regarding training optimisation and the efficacy of SH education methods.
A framework for selection of high-yielding and drought-tolerant genotypes of barley: Applying yield- based indices and multi-index selection models
Authors: Ghazvini Habibollah , Pour-Aboughadareh Alireza , Jasemi Seyed Shahriyar , Chaichi Mehrdad , Tajali Hamid , Bocianowski Jan
Published: February 2024

Drought stress is one of the major environmental stresses that dramatically reduces agricultural production around the world. Barley (Hordeum vulgare L.) plays an important role in both food and feed security. The objective of this study was to identify the superior drought-tolerant genotypes using grain yield and several yield-based indices of tolerance and susceptibility by applying various multivariate selection models. To achieve this objective, a set of promising new barley genotypes was evaluated in three drought-prone regions of Iran (Mashhad, Karaj, and Hamadan) during two consecutive growing seasons (2019–2020 and 2020–2021). The results of additive main effect and multiplicative interaction (AMMI) analysis showed significant effects for genotypes (G), environments (E), and their interaction (G×E). Based on the AMMI model, G3, G7, G9, and G13 were identified as the four highest-ranked genotypes in terms of grain yield. Based on the Smith-Hazel, factor analysis and genotype-ideotype distance index (FAI), and genotype–ideotype distance index (MGIDI) selection models, genotypes G4 and G13 showed the greatest tolerance to drought stress conditions in the three regions. Moreover, the most significant selection gain was found for the stress tolerance index, yield index, and grain yield under drought stress conditions (Ys). The results of the genotype (G) + genotype × environment (GGE) biplot analysis coincided with those obtained, in which the G4 and G13 genotypes showed specific adaptability in drought environments. In addition, among the environments tested, the Karaj region was selected as an ideal target environment with significant discriminatory power and representative ability. In conclusion, the collective analysis using the AMMI, GGE biplot, and multi-index selection models identified genotypes G4 and G13 as superior genotypes. Consequently, these genotypes may be candidates for commercial introduction.
Comparative Analysis of XAI Techniques on Telecom Churn Prediction Using SHAP and Interpreted ML Partial Dependence
Authors: ÖZKURT Cem
Published: February 2024

This paper conducts a comparative analysis of two prominent Explainable Artificial Intelligence (XAI) techniques, SHAP (SHapley Additive exPlanations) and Interpreted ML Partial Dependence, applied to a Telecom Churn dataset. The objective is to assess and contrast these techniques in enhancing transparency and interpretability of machine learning models, specifically in telecom churn prediction. The study emphasizes the significance of XAI in ensuring trust and comprehension in predictive modeling. The methodology outlines dataset preprocessing and model training steps. Two separate analyses using SHAP and Interpreted ML Partial Dependence are conducted to evaluate their effectiveness in elucidating model decisions and uncovering feature importance. Results, strengths, and limitations of both techniques are discussed, providing valuable insights into interpretability and robustness. The comparative analysis contributes to understanding XAI methods, emphasizing the importance of selecting appropriate techniques based on context and goals in enhancing transparency in telecom churn prediction models.
Energy Efficient 6G performance Improvement based on Service Level Recursive Scheduling routing using Priority cycle Tags (PCT)
Authors: E Sangeetha , J Deny
Published: February 2024

The Sixth Generation (6G) mobile communication system is actively promoted worldwide. One solution for ultra-high-speed communications is to use the ter-ahertz frequency band above 100 GHz. This is due to the availability of wider frequency bands than 5G. Due to the increasing performance of network issues in the transmission path, data may be leaked or injected incorrectly. Therefore, the performance of the routing network is significant for centralized routing, improving data transmission and preventing malicious activity. To overcome the issues, this work proposed the method of Enhance Service Data Transmission (ESDT) using Energy Optimized Network Route Cluster Bandwidth (EONRCB) transmission based on slicing the nearest neighbor and splitting the route in a 6G network. Initially, the traffic routing is checked based on the Transmission Node Support Weight (TNSW). Each node must constantly authenticate access control to fragment the data in packets, and access control is detected based on routing as needed. Service Level Route Count Rollback Node Aggregator (SLR-CRNA) improves the network’s performance by verifying active node exchanges. The sleeper node controller then preserves the node’s response behaviour and sends the data to the current location of the trusted node exchange. Slicing Neighbor Node Path Routing (SN2PR) also establishes connectivity between sources to 1 destination nodes in Edge Networks. Then scheduling the node priority based to enable the network to avoid the traffic in the frequency of the network based on the Priority cycle Tags (PCT) using Recursive Scheduling Time (RST) provides an optimal scheduling policy by iteratively adjusting the duration of tasks until time mismatch is minimized. RTSS can be achieved in 6G wireless networks with minimal changes in planning architecture. Performance evaluations show the effectiveness of the proposed scheme in reducing misalignment delays for random traffic periods. Service Level Route Count Rollback Node Aggregator (SLR-CRNA) is attained to avoid traffic, improve energy efficiency, and schedule the nodes with limited time transmission to assign the route and enhance network lifetime and performance. The proposed 6G-the framework has been implemented in the 6G network Time-based scheduling. It provides high network performance and has been validated by comparing the values with other methods.
An Autonomous Blockchain-Based Workflow Execution Broker for e-Science
Authors: Alimoglu Alper , Ozturan Can
Published: February 2024

Scientific workflows are essential for many applications, enabling the configuration and execution of complex tasks across distributed resources. In this paper, we contribute an Ethereum blockchain-based scientific workflow execution manager, which distributes workflows to run on cluster computing providers that utilize the Slurm workload manager to execute them. We extended our blockchain-based autonomous resource broker called eBlocBroker, which is a DAO-based decentralized coordinator, by providing distributed workflow execution via blockchain. Through various tests, we demonstrate how our eBlockBroker autonomous organization, which is programmed as a smart contract, can manage scientific workflow submission, scheduling, and execution on cluster computing providers. We are motivated because our system has been developed with e-Science in mind where scientific workflows are widely utilized.
Predictive Analysis of Breast Cancer Response to Neoadjuvant Chemotherapy through Plasma Metabolomics
Authors: Yamada Miki , Jinno Hiromitsu , Naruse Saki , Isono Yuka , Maeda Yuka , Sato Ayana , Matsumoto Akiko , Ikeda Tatsuhiko , Sugimoto Masahiro
Published: February 2024

Purpose
Preoperative chemotherapy is a critical component of breast cancer management, yet its effectiveness is not uniform. Moreover, the adverse effects associated with chemotherapy necessitate the identification of a patient subgroup that would derive the maximum benefit from this treatment. This study aimed to establish a method for predicting the response to preoperative chemotherapy in breast cancer patients utilizing metabolomics.
Methods
Plasma samples were obtained from 87 breast cancer patients undergoing preoperative chemotherapy at our facility, collected both prior to the commencement of the treatment and before the second treatment cycle. Metabolite analysis was conducted using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS). We performed comparative profiling of metabolite concentrations by assessing the metabolite profiles of patients who achieved a pathological complete response (pCR) against those who did not, both in initial and subsequent treatment cycles.
Results
Significant variances were observed in the metabolite profiles between pCR and non-pCR cases, both at the onset of preoperative chemotherapy and before the second cycle. Noteworthy distinctions were also evident between the metabolite profiles from the initial and the second preoperative chemotherapy courses. Furthermore, metabolite profiles exhibited variations associated with intrinsic subtypes at all assessed time points.
Conclusion
The application of plasma metabolomics, utilizing CE-MS and LC-MS, has proven to be an effective approach for predicting the efficacy of preoperative chemotherapy in breast cancer.
Editorial: Digitalisierung in der Administration österreichischer Hochschulen (2020–2024)
Authors: Rieger Elisabeth , Watzinger Lea
Published: February 2024

Das Bundesministerium für Bildung, Wissenschaft und Forschung (BMBWF) hat 2020 im Rahmen der österreichweiten Ausschreibung „Vorhaben zur digitalen und sozialen Transformation in der Hochschulbildung“ insgesamt 50 Millionen Euro Fördermittel für 34 in einem Begutachtungsverfahren ausgewählte Projekte vergeben. Gefördert werden zukunftsweisende Kooperationsprojekte, die den Anspruch haben, innerhalb ihrer Laufzeit bis 2024 strukturverändernd in das Universitätssystem hineinzuwirken. Die Zeitschrift ZFHE bietet ausgewählten Projekten durch drei Sonderausgaben die Gelegenheit, ihre Ergebnisse und Erfahrungen in einem Open-Access-Format einem breiten, auch wissenschaftlichen Publikum vorzustellen. Die Sonderhefte setzen ihren Fokus auf die Bereiche Lehre, Forschung und Administration. In dieser Ausgabe liegt der Schwerpunkt auf Projekten im administrativen Kontext, die alle Handlungsfelder – Lehre, Forschung, Verwaltung und 3rd Mission – abdecken. Überdies wird die Erforschung hochschulübergreifender und interdisziplinärer KI-basierter Systeme in den Fokus genommen.