bluuebunny/crossref_metadata_2025_split huggingface dataset:
Importance of Per2 in cardiac mitochondrial protection during stress
Authors: Bhaskara Meghana , Anjorin Olufisayo , Yoniles Arris , Liu Jianyun , Wang Meijing 
Published: January 2024

AbstractDuring myocardial injury, inflammatory mediators and oxidative stress significantly increase to impair cardiac mitochondria. Emerging evidence has highlighted interplays between circadian protein—period 2 (Per2) and mitochondrial metabolism. However, besides circadian rhythm regulation, the direct role of Per2 in mitochondrial performance particularly following acute stress, remains unknown. In this study, we aim to determine the importance of Per2 protein’s regulatory role in mitochondrial function following exposure to inflammatory cytokine TNFα and oxidative stressor H2O2 in human cardiomyocytes. Global warm ischemia (37 °C) significantly impaired complex I activity with concurrently reduced mitochondrial Per2 in adult mouse hearts. TNFα or H2O2 decreased Per2 protein levels and damaged mitochondrial respiratory function in adult mouse cardiomyocytes. Next, mitochondrial membrane potential ($$\Delta \psi$$

Δ
ψ

M) using JC-1 fluorescence probe and mitochondrial respiration capacity via Seahorse Cell Mito Stress Test were then detected in Per2 or control siRNA transfected AC16 Human Cardiomyocytes (HCM) that were subjected to 2 h-treatment of TNFα (100 ng/ml) or H2O2 (100 μM). After 4 h-treatment, cell death was also measured using Annexin V and propidium iodide apoptosis kit through flow cytometry. We found that knockdown of Per2 enhanced TNFα-induced cell death and TNFα- or H2O2-disrupted $$\Delta \psi$$

Δ
ψ

M, as well as TNFα- or H2O2-impaired mitochondrial respiration function. In conclusion, Per2 knockdown increases likelihood of cell death and mitochondrial dysfunction in human cardiomyocytes exposed to either TNFα or H2O2, supporting the protective role of Per2 in HCM during stress with a focus on mitochondrial function.
Preparation of stable colloidal dispersion of surface modified Fe3O4 nanoparticles for magnetic heating applications
Authors: Sabzi Dizajyekan Behnam , Jafari Arezou , Vafaie-Sefti Mohsen , Saber Reza , Fakhroueian Zahra 
Published: January 2024

AbstractThe effect of surface modification on enhancing the magnetic heating behavior of magnetic nano fluids were investigated, for this purpose Fe3O4 nanoparticles were synthesized using co-precipitation method and surface modification was done using citric acid, ascorbic acid, tetraethyl orthosilicate (TEOS), polyvinyl alcohol (PVA) and polyethylene glycol (PEG). Experimental heating tests using AC magnetic field were done in the frequency of 100 kHz and different magnetic field (H) intensities. Theoretically the specific absorption rate (SAR) in magnetic nano fluids is independent of nanoparticles concentration but the experimental results showed different behavior. The theoretical SAR value @ H = 12kA.m–1 for Nano fluids containing bare Fe3O4 nanoparticles was 11.5 W/g but in experimental tests the obtained value was 9.72 W/g for nano fluid containing 20,000 ppm of dispersed nanoparticles. The experimental SAR calculation was repeated for sample containing 10,000 ppm of nanoparticles and the results showed increase in experimental SAR that is an evidence of nanoparticles agglomeration in higher concentrations. The surface modification has improved the dispersion ability of the nanoparticles. The Ratio of SAR, experimental, 20000ppm to SAR, experimental, 10000ppm was 0.85 for bare Fe3O4 nanoparticles dispersion but in case of surface modified nanoparticles this ratio has increased up to 0.98 that shows lower agglomeration of nanoparticles as a result of surface modification, although on the other hand the surface modification agents were magnetically passive and so it is expected that in constant concentration the SAR for bare Fe3O4 nanoparticles to be higher than this variable for surface modified nanoparticles. At lower concentrations the dispersions containing bare Fe3O4 nanoparticles showed higher SAR values but at higher concentrations the surface modified Fe3O4 nanoparticles showed better results although the active agent amount was lower at them. Finally, it should be noted that the nanoparticles that were surface modified using polymeric agents showed the highest decrease in experimental SAR amounts comparing theoretical results that was because of the large molecules of polymers comparing other implemented surface modification agents.
Serum uric acid is inversely associated with lung function in US adults
Authors: Luo Wen , Wang Chen , Wang Wanyu , Yao Xiangyang , Lu Fang , Wu Dinghui , Lin Yihua 
Published: January 2024

AbstractThe relationship between serum uric acid and lung function has been controversial. This study aims to determine whether there is an independent relationship between serum uric acid and lung function in the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2012. Serum uric acid was considered the exposure variable, and lung function (FEV1 and FVC) was the outcome variable. Multivariable linear regression was conducted with adjustments for potential confounders. The total number of participants from NHANES (2007–2012) was 30,442, of which 7514 were included in our analysis after applying exclusion criteria. We observed that serum uric acid was negatively associated with FEV1 and FVC after adjusting for confounders (β for FEV1 [− 24.77 (− 36.11, − 13.43)] and FVC [− 32.93 (− 47.42, − 18.45)]). Similarly, serum uric acid showed a negative correlation with FEV1 and FVC after adjusting for confounding variables both in male and female populations. The relationship between serum uric acid and FEV1 and FVC remained consistent and robust in various subgroups within both male and female populations, including age, race, BMI, alcohol consumption, smoking status, and income-poverty ratio. Serum uric acid is negatively associated with FEV1 and FVC in the US general healthy population. This negative relationship is significant in both the male and female populations.
Two-substrate enzyme engineering using small libraries that combine the substrate preferences from two different variant lineages
Authors: Mukhopadhyay Arka , Karu Kersti , Dalby Paul A. 
Published: January 2024

AbstractImproving the range of substrates accepted by enzymes with high catalytic activity remains an important goal for the industrialisation of biocatalysis. Many enzymes catalyse two-substrate reactions which increases the complexity in engineering them for the synthesis of alternative products. Often mutations are found independently that can improve the acceptance of alternatives to each of the two substrates. Ideally, we would be able to combine mutations identified for each of the two alternative substrates, and so reprogramme new enzyme variants that synthesise specific products from their respective two-substrate combinations. However, as we have previously observed for E. coli transketolase, the mutations that improved activity towards aromatic acceptor aldehydes, did not successfully recombine with mutations that switched the donor substrate to pyruvate. This likely results from several active site residues having multiple roles that can affect both of the substrates, as well as structural interactions between the mutations themselves. Here, we have designed small libraries, including both natural and non-natural amino acids, based on the previous mutational sites that impact on acceptance of the two substrates, to achieve up to 630× increases in kcat for the reaction with 3-formylbenzoic acid (3-FBA) and pyruvate. Computational docking was able to determine how the mutations shaped the active site to improve the proximity of the 3-FBA substrate relative to the enamine-TPP intermediate, formed after the initial reaction with pyruvate. This work opens the way for small libraries to rapidly reprogramme enzyme active sites in a plug and play approach to catalyse new combinations of two-substrate reactions.
Modelling the wind potential energy for metallurgical sector in Albania
Authors: Dhoska Klodian , Bebi Elena , Markja Irida , Milo Parid , Sita Ermil , Qosja Serxhi 
Published: January 2024

AbstractThe metallurgical industry, in the context of the global energy crisis and the new European green deal, needs urgent investments on energy and resource efficiency. The metallurgical sector, which includes the production of different metals is an energy-intensive industry that requires large amounts of energy for various processes such as smelting, refining, and casting. One of the largest consumptions of energy in Albania comes from the metallurgical sector during the production of iron, steel, chromium and aluminum which corresponds respectively to three private companies called “Kurum International Ltd”, “AlbChorme Ltd” and “Everest Ltd”. During the last three years, these companies have temporary interrupted the production process due to the higher electricity price that come from imports. Based on it, our research work presents the energy efficiency analysis in the Albanian metallurgical sector by focusing on the implementation of wind energy in the above mentioned private metallurgical companies, because adding new generation capacity from Renewable Energy Sources in a context of industrial energy communities, will contribute to improve the security of supply for this industry. The Wind Balkan Atlas, New European Wind Atlas, and Wind Atlas Analysis and Application Program (WAsP) has been used to select the appropriate areas and to develop the wind potential distribution maps, as well as to select the most suitable type of wind turbine based on capacity factors. Two areas were selected close to the metallurgical sectors in the regions of “Vajkal” in Bulqizë and “Selitë e Malit” in Tirana. It has been installed the power of 9 MW for each wind farm, with a capacity factor of 40% and 36.6% respectively, and with a total annual energy production of about 60 GWh/year, these wind farms will cover about 26% of the total annual consumption of companies. Clean Energy Management Software (RETScreen Expert) was used for the detailed economic analysis and environmental impact of proposed wind farms. The economic sensitivity analysis of the proposed wind farms showed that even for the highest installation cost value of 1350 €/kW, for discount rates 5, 7, and 11%, the LCoE values are within the statistically established range for wind farms in Europe.
Silver nanoparticles improve the fungicidal properties of Rhazya stricta decne aqueous extract against plant pathogens
Authors: Al-Sahli Sarah A. , Al-Otibi Fatimah , Alharbi Raedah I. , Amina Musarat , Al Musayeib Nawal M. 
Published: January 2024

AbstractOne of the most promising, non-toxic, and biocompatible developments for many biological activities is the green synthesis of nanoparticles from plants. In this work, we investigated the antifungal activity of silver nanoparticles (AgNPs) biosynthesized from Rhazya stricta aqueous extract against several plant pathogenic fungi. UV–visible spectroscopy, Zeta potential analysis, Fourier-transform infrared spectroscopy (FTIR), and transmitted electron microscopy (TEM) were used to analyze the biosynthesized AgNPs. Drechslera halodes, Drechslera tetramera, Macrophomina phaseolina, Alternaria alternata, and Curvularia australiensis were tested for their potential antifungal activity. Surface Plasmon Resonance (SPR) of Aq. AgNPs and Alkaline Aq. AgNPs was observed at 405 nm and 415 nm, respectively. FTIR analysis indicated hydroxyl, nitrile, amine, and ketone functional groups. Aq. AgNPs and Alka-line Aq. AgNPs had velocities of − 27.7 mV and − 37.9 mV and sizes of 21–90 nm and 7.2–25.3 nm, respectively, according to zeta potential studies and TEM. The antifungal examination revealed that all species' mycelial development was significantly inhibited, accompanied by severe ultra-structural alterations. Among all treatments, Aq. AgNPs were the most effective fungicide. M. phaseolina was statistically the most resistant, whereas A. alternata was the most vulnerable. To the best of our knowledge, this is the first report on R. stricta's antifungal activity against these species.
QEEG findings in nonsyndromic sagittal craniosynostosis
Authors: Skadorwa Tymon , Strzelecka Jolanta 
Published: January 2024

AbstractDespite the undertaken treatment, children with nonsyndromic sagittal craniosynostosis (NSC) are burdened with problems with speech development, visuospatial and other cognitive deficits. The electroencephalographic assessment has not influenced the diagnostics and treatment strategy of craniosynostosis so far but the introduction of quantitative EEG (QEEG) protocols renewed an interest in the functional aspect of this disease. In this study we retrospectively assessed the QEEG records of 25 children with NSC aged 1–18 months (mean age 9.62 months) before and after surgery. In each case, the amplitude, interhemispheric (ICoh) and intrahemispheric (HCoh) coherence indices were calculated. Obtained data were compared to age-matched control group of 25 normocephalic children. Children with NSC presented significantly lower values of amplitudes and intrahemispheric coherence in occipital, posterior parietal and posterior temporal regions than normocephalic children. The values of amplitudes, ICoh and HCoh in pre- and postoperative QEEG records mostly remained unchanged, with a slight improvement in HCoh in centro-parietal area. These findings suggest that NSC children present their own QEEG profile. The operative treatment improves an intrahemispheric connectivity, but there still exists a significant difference in the occipitotemporal, frontotemporal and centro-frontal areas, which may be considered as a functional substrate of reported speech and neurocognitive problems. QEEG findings in nonsyndromic sagittal craniosynostosis.
Screening patients requiring secondary lumbar surgery for degenerative lumbar spine diseases: a nationwide sample cohort study
Authors: Park Hangeul , Lee Juhee , Choi Yunhee , Kim Jun-Hoe , Kim Sum , Kim Young-Rak , Lee Chang-Hyun , Park Sung Bae , Kim Kyoung-Tae , Rhee John M. , Kim Chi Heon 
Published: January 2024

AbstractThis study aims to identify healthcare costs indicators predicting secondary surgery for degenerative lumbar spine disease (DLSD), which significantly impacts healthcare budgets. Analyzing data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC) database of Republic of Korea (ROK), the study included 3881 patients who had surgery for lumbar disc herniation (LDH), lumbar spinal stenosis without spondylolisthesis (LSS without SPL), lumbar spinal stenosis with spondylolisthesis (LSS with SPL), and spondylolysis (SP) from 2006 to 2008. Patients were categorized into two groups: those undergoing secondary surgery (S-group) and those not (NS-group). Surgical and interim costs were compared, with S-group having higher secondary surgery costs ($1829.59 vs $1618.40 in NS-group, P = 0.002) and higher interim costs ($30.03; 1.86% of initial surgery costs vs $16.09; 0.99% of initial surgery costs in NS-group, P < 0.0001). The same trend was observed in LDH, LSS without SPL, and LSS with SPL (P < 0.0001). Monitoring interim costs trends post-initial surgery can effectively identify patients requiring secondary surgery.
Fertility detection of unincubated chicken eggs by hyperspectral transmission imaging in the Vis-SWNIR region
Authors: Ghaderi Mahdi , Mireei Seyed Ahmad , Masoumi Aminollah , Sedghi Mohammad , Nazeri Majid 
Published: January 2024

AbstractDetection of infertile eggs prior to incubation can lead to an increase in the hatchability rate and prevent the wastage of billions of non-fertile eggs ended up by failed incubation. In this study, the feasibility of a line-scan hyperspectral imaging system in the visible and short-wavelength near-infrared region was assessed for early detection of non-fertile eggs on day 0 before incubation. A total of 227 white-shell eggs including 131 fertile and 96 infertile eggs were collected from a flock with similar conditions in terms of hen age, feeding, and management. Hyperspectral images of eggs were captured on day 0 before incubation in a transmittance mode of illumination and then the eggs were incubated in a commercial incubator. The edge detection method was used to segment the egg, including both the white and yolk, from the background, and the image spectral information was extracted from the egg region. After applying various pretreatment methods, different classifiers including soft independent modeling of class analogy (SIMCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and artificial neural networks (ANN) classifiers were utilized to extract the predictive models. Following the acceptable results of SIMCA analysis accomplished by 1st derivative pretreatment (accuracy of 86.67%), the discrimination power plot was used to select the most informative wavebands. The results showed that by using fewer variables in effective wavebands better performance (precision and accuracy of 92.59% and 93.33%, respectively) could be obtained in comparison with the ANN classifier based on the whole spectral data (precision and accuracy of 89.29% and 91.11%, respectively). This study revealed the potential application of hyperspectral transmittance imaging in the Vis-SWNIR region to discern the fertile and infertile eggs before starting the incubation process.
Edge computing-based proactive control method for industrial product manufacturing quality prediction
Authors: Chen Mo , Wei Zhe , Li Li , Zhang Kai 
Published: January 2024

AbstractWith the emergence of intelligent manufacturing, new-generation information technologies such as big data and artificial intelligence are rapidly integrating with the manufacturing industry. One of the primary applications is to assist manufacturing plants in predicting product quality. Traditional predictive models primarily focus on establishing high-precision classification or regression models, with less emphasis on imbalanced data. This is a specific but common scenario in practical industrial environments concerning quality prediction. A SMOTE-XGboost quality prediction active control method based on joint optimization hyperparameters is proposed to address the problem of imbalanced data classification in product quality prediction. In addition, edge computing technology is introduced to address issues in industrial manufacturing, such as the large bandwidth load and resource limitations associated with traditional cloud computing models. Finally, the practicality and effectiveness of the proposed method are validated through a case study of the brake disc production line. Experimental results indicate that the proposed method outperforms other classification methods in brake disc quality prediction.
IDSL.GOA: gene ontology analysis for interpreting metabolomic datasets
Authors: Mahajan Priyanka , Fiehn Oliver , Barupal Dinesh 
Published: January 2024

AbstractBiological interpretation of metabolomic datasets often ends at a pathway analysis step to find the over-represented metabolic pathways in the list of statistically significant metabolites. However, definitions of biochemical pathways and metabolite coverage vary among different curated databases, leading to missed interpretations. For the lists of genes, transcripts and proteins, Gene Ontology (GO) terms over-presentation analysis has become a standardized approach for biological interpretation. But, GO analysis has not been achieved for metabolomic datasets. We present a new knowledgebase (KB) and the online tool, Gene Ontology Analysis by the Integrated Data Science Laboratory for Metabolomics and Exposomics (IDSL.GOA) to conduct GO over-representation analysis for a metabolite list. The IDSL.GOA KB covers 2393 metabolic GO terms and associated 3144 genes, 1,492 EC annotations, and 2621 metabolites. IDSL.GOA analysis of a case study of older versus young female brain cortex metabolome highlighted 82 GO terms being significantly overrepresented (FDR < 0.05). We showed how IDSL.GOA identified key and relevant GO metabolic processes that were not yet covered in other pathway databases. Overall, we suggest that interpretation of metabolite lists should not be limited to only pathway maps and can also leverage GO terms as well. IDSL.GOA provides a useful tool for this purpose, allowing for a more comprehensive and accurate analysis of metabolite pathway data. IDSL.GOA tool can be accessed at https://goa.idsl.me/.
ALKBH5 is a prognostic factor and promotes the angiogenesis of glioblastoma
Authors: Fan Yugeng , Yan Dujuan , Ma Lijun , Liu Xiaoxi , Luo Guoqiang , Hu Yan , Kou Xin 
Published: January 2024

AbstractDespite numerous reports indicating the significant impact of RNA modification on malignant glioblastoma (GBM) cell behaviors such as proliferation, invasion and therapy efficacy, its specific involvement in glioblastoma (GBM) angiogenesis is remains unclear and is currently under investigation. In this study, we aimed to investigate the relevance between RNA modification regulators and GBM angiogenesis. Our study employed bioinformatic analyses, including Gene Set Enrichment Analysis (GSEA), differential expression analysis, and Kaplan–Meier survival analysis, to identify regulators of angiogenesis-associated RNA modification (RM). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to identify the enrichment of angiogenesis associated signatures in ALKBH5-high expression GBMs. We also utilized Western blot to verify the upregulation of ALKBH5 in clinical GBM samples. By a series of in vitro and in vivo assays, including plasmid transfection, wound healing, transwell invasion test, tube formation, RT-qPCR, ELISA assays and xenograft mice model, we validated the angiogenesis regulation ability of ALKBH5 in GBM. The N6-methyladenosine (m6A) modification “erase” ALKBH5 emerged as a candidate regulator associated with angiogenesis, demonstrating elevated expression and robust prognostic predictive ability in GBM patients. We also revealed enrichment of vasculature development biological process in GBMs with high ALKBH5 expression. Subsequently, we validated the elevated the expression of ALKBH5 in clinical GBM and paired adjacent tissues through western blot. Additionally, we knocked down the expression of ALKBH5 using sh-RNAs in U87 GBM cells to access the angiogenesis induction ability in U87 cells. In vitro experiments, Human Umbilical Vein Endothelial Cells (HUVECs) were used to perform wound healing, transwell migration and tube formation analysis, results indicated that ALKBH5 knock-down of U87 cells could decrease the pro-angiogenesis ability of U87 GBM cells. Further validation of our bioinformatic findings confirmed that ALKBH5 knockdown impaired VEGFA secretion in both in vitro and in vivo settings in U87 cells. These results comprehensively affirm the crucial role of ALKBH5 in regulating GBM-induced angiogenesis, both in vitro and in vivo. ALKBH5 not only emerges as a promising prognostic factor for GBM patients, but also plays a pivotal role in sustaining GBM progression by promoting angiogenesis.