bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the bioactives and the mechanism of Aegle marmelos in the treatment of Inflammatory bowel disease through network pharmacology and molecular docking approach
Authors: Shah Bhagyabhumi , Solanki Nilay 
Published: October 2023

Abstract
Inflammatory bowel diseases (IBD) are recurrent inflammatory conditions that occur in the gastrointestinal tract, and current treatment does not have satisfactory results, we still need newer therapies to combat the complex pathogenesis of IBD. Herbal medicines have been used for years to cure IBD. One of the plants from Ayurveda, Aegle marmelos (AM), commonly known as Bael and belonging to the family Rutaceae has ethnomedicinal properties in treating IBD due to its various phytochemicals. However, the mechanisms underlying the effect of AM remain to be elucidated. In the study, 46 effective compounds and 358 targets of AM were identified and further analyzed, 80 hub targets depending on the degree were considered effective against IBD. Through the Cyto Hubba plugin of Cytoscape (3.10.0), we identified AKT1, SRC, MAPK3, MAPK1, EGFR, IL6, TNF, HSP90AA1, and CASP3 as the top 10 hub targets that may contribute to the mechanistic role of AM in treating IBD. Aegeline, auraptene, bergapten, imperatorin, marmesin, and nodakenin were the potent compounds of AM and the molecular docking studies with the hub target depict their higher binding affinity to PI3K, AKT, and EGFR. The Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis suggest that PI3-AKT signaling pathway, EGFR tyrosine kinase inhibitor, and MAP Kinase signaling pathway are the major pathways correlating with AM in combating IBD. The network pharmacological and molecular docking approach unveils the mechanism of AM in alleviating IBD through the EGFR-mediated PI3K/AKT pathway, stating its multi-component, multi-targeted therapeutic efficacy through multiple pathways.
Sudan Blue II Dye loaded modified MCM-48: Colorimetric, Paper Strip, and Fluorescent Sensor for Cu 2+ ion
Authors: Kalita Sarojmoni , Das Diganta Kumar 
Published: October 2023

Abstract
In this work, Sudan Blue II dye is successfully grafted on the walls of chloro-functionalised MCM-48. The synthesized probe selectively detect Cu2+ ion by fluorescence spectroscopy. The probe designated as SB@modMCM-48 was characterized by various spectroscopic methods including FT-IR, SEM, EDX and N2 adsorption-desorption isotherm, etc. The fluorescent intensity of the probe is quenched by 14 times in presence of Cu2+ ion. The fluorescent detection is reversible, selective with low detection limits. The LOD and Ka (association constant) was calculated to be 1.45 × 10− 10 M and 5.38 × 107 M− 1 respectively with a linear range of detection. The addition of Cu2+ ion to the probe solution also imparted a visual color change. Paper strip sensor was also developed for naked eye detection of Cu2+. The low LOD limits, binding stoichiometric constant, etc. point towards high affinity of Cu2+ towards the nanosensor. Interestingly, the Cu2+:sensor complex selectively sense amino acid cysteine in its aqueous solution, with a limit of detection of 10.46 × 10− 8 M.
Extraction of cellulose microfibers from waste fallen leaves and fabrication of a degradable composite film for packaging applications
Authors: Chanthavong Vinitsa , Prabhakar M. N. , Lee Dong-Woo , Song Jung Il 
Published: October 2023

Abstract
The plastics industry is increasingly using renewable natural polymers, with cellulose being the most popular choice because of its large market size of 211 billion USD. Nonetheless, the extraction of cellulose in economically viable forms, especially in micro- and nanoforms, continues to pose a challenge for researchers. To address this issue, a recent study focused on extracting cellulose microfibers (CMFs) from agro biomass to reduce costs. Alkaline peroxide treatment was used to extract microcellulose from waste fallen dried leaves. The resultant CMFs were 45.8 µm in size, with spectral peaks of 3,339 cm− 1 and 2,890 cm− 1 corresponding to the hydrogen bond O-H, and C-H of cellulose respectively. CMFs were used to reinforce polyvinyl alcohol (PVA) and make CMF/PVA composite films using the solution casting method. Various percentages of CMFs (5–15%) were tested, with the resultant composites having chemical interaction bonds at 3,260 cm− 1 and 2θ = 19.6° diffraction peaks. The tensile strengths of the optimized CMFs were 80.37 MPa and 2.51 GPa, accompanied by a decrease of 9.37% elongation at break. The CMFs significantly enhanced biodegradation by approximately 21.44%, highlighting their potential environmental benefits in plastic film production. In summary, this study provides insights into economically obtaining microcellulose and designing biodegradable plastics for packaging applications. The utilization of renewable natural polymers such as cellulose in the plastic industry is imperative for promoting eco-friendly practices. The findings of this study offer a promising solution for this problem.
All lactose-oxidizing enzymes of Pseudomonas taetrolens, a highly efficient lactobionic acid-producing microorganism, are pyrroloquinoline quinone- dependent enzymes
Authors: Lee Seung Soo , Oh Yu-Ri , Jang Young-Ah , Han So Yeon , Eom Gyeong Tae 
Published: October 2023

Abstract
In previous and present studies, four enzymes (GCD1, GCD3, GCD4, and MQO1) have been found to act as lactose-oxidizing enzymes of Pseudomonas taetrolens. To investigate whether the four enzymes were the only lactose-oxidizing enzymes of P. taetrolens, we inactivated gcd1 and gcd4 of P. taetrolens ∆gcd3 ∆mqo1. Compared to the wild-type strain, the lactobionic acid (LBA)-producing ability of P. taetrolens ∆gcd1 ∆gcd3 ∆gcd4 ∆mqo1 was only slightly decreased, implying that P. taetrolens possesses more lactose-oxidizing enzymes. Interestingly, the four lactose-oxidizing enzymes were all PQQ-dependent. To identify other unidentified lactose-oxidizing enzymes of P. taetrolens, we prevented the synthesis of PQQ in P. taetrolens by inactivating the genes related to PQQ synthesis such as pqqC, pqqD, and pqqE. Surprisingly, all three knocked-out strains were unable to convert lactose to LBA, indicating that all lactose-oxidizing enzymes in P. taetrolens were inactivated by eliminating PQQ synthesis. In addition, external PQQ supplementation restored the LBA production ability of P. taetrolens ∆pqqC, comparable to the wild-type strain. These results indicate that all lactose-oxidizing enzymes in P. taetrolens are PQQ-dependent.
Interpretable Machine Learning in Predicting Drug-Induced Liver Injury among Tuberculosis Patients: Model Development and Validation Study
Authors: Xiao Yue , Chen Yanfei , Huang Ruijian , Jiang Feng , Zhou Jifang , Yang Tianchi 
Published: October 2023

Abstract

Background: This study aimed to develop and validate an interpretable prediction model for Drug-Induced Liver Injury during tuberculosis treatment.
Methods: Using a dataset of TB patients from Ningbo City, the models were developed using eXtreme Gradient Boosting, random forest, and logistic regression algorithms. Features were selected using the Least Absolute Shrinkage and Selection Operator method. The model's performance was assessed through various metrics, including receiver operating characteristic and precision-recall curves. Calibration and clinical utility were also evaluated. Variable contributions were interpreted using SHapley Additive exPlanations and Partial Dependence plots.
Results: Of 7,071 TB patients (median age: 47 years; 68.0% male), 16.3% developed DILI. Calibration showed minimal brier score differences among algorithms (0.003 to 0.004). XGBoost had the highest recall at 0.742, while random forest and logistic regression posted 0.675 and 0.649, respectively. All models demonstrated enhanced clinical utility in the validation set. SHAP analysis for XGBoost highlighted prior DILI instances as a significant risk. Elevated alanine aminotransferase ratios were linked to DILI in both XGBoost and random forest models.
Conclusion: In conclusion, this study introduces an interpretable prediction model for assessing DILI risk among TB patients. The model's interpretability shed light on the significance of patients' disease history and ALT levels. This model holds potential for advancing personalized risk assessment and enhancing patient care in the context of TB treatment.
Assessing the conformity of single-use food plastic packaging products to the applicable standards: A seven-year study of tests conducted at the Ghana Standards Authority
Authors: Kwansa Victor Charles , Essandoh Helen M. , Dwumfour-Asare Bismark , Awuah Esi 
Published: October 2023

Abstract
Widely used single-use food plastic packaging products in Ghana present health and safety risks to consumers. The study analyses seven years of data from the Ghana Standards Authority Polymer laboratory to identify food plastic packaging product types used in Ghana and non-conformities with GS 173:2018 and GS 1186:2018. Employing a retrospective design, as well as descriptive, correlational, regression, ANOVA, and risk assessment analyses, the research evaluates the safety and quality of single-use food plastic packaging products tested from 2016 to 2022. According to the data, recycled PE Carrier Bags accounted for 50.2%, while HDPE and LDPE plastics comprised 37.1% and 12.7%, respectively. The regression analysis emphasized the importance of controlling thickness in plastic manufacturing to ensure desired Elongation at Break and Tensile Strength properties. The overall migration of non-volatile residues from the single-use HDPE, LDPE, and recycled PE Carrier bag products using Acetic Acid and Ethanol showed no statistically significant difference. The study concludes that plastic packaging for food in Ghana is safe, as non-volatile residue migration well below the 5mg/l maximum specification. The GSA and other relevant stakeholders need to remain vigilant and undertake continuous monitoring and surveillance to ensure overall product safety and compliance to standards.
Gut microbiome composition is related to anxiety and aggression score in companion dogs
Authors: Pellowe Sarita D. , Zhang Allan , Bignell Dawn R. D. , Peña-Castillo Lourdes , Walsh Carolyn J. 
Published: October 2023

Abstract

Background
There is mounting evidence for a link between behaviour and gut microbiome composition in several animal models and human health. However, the role of the gut microbiota in the development and severity of behavioural issues in companion dogs is not yet fully understood. In this work, we investigated the relationship between gut microbiome composition and aggression or anxiety in pet dogs. Pet dogs (n = 48) were assigned to higher or lower anxiety and aggression groups based on their owner’s responses to the Canine Behavioral Assessment & Research Questionnaire (C-BARQ). Then the gut microbiome of each animal, sequenced from microbial DNA extracted from fecal samples, was assessed for association with the dog’s assigned behavioural group using multiple approaches.
Results
While minimal differences in relative abundance were seen between behavioural groups, we were successful in predicting behavioural group based on gut microbiome composition using machine-learning based approaches and compositional balances. The generated models were particularly successful when distinguishing higher and lower anxiety dogs. The genus Blautia was identified across all our analyses, suggesting a strong link between this genus and anxiety in pet dogs.
Conclusions
This study builds on a growing area of research of great interest to dog owners, trainers, and behaviour professionals, and provides insight into specific bacteria that are linked to increased anxiety and aggression in pet dogs. Further research is required to identify bacteria to the species level, and to better understand the specific role of Blautia in the canine gut-brain axis.
Severe convective storms' reproduction: Empirical analysis from the marked self-exciting point processes point of view
Authors: Galbo Giada Lo , Chiodi Marcello 
Published: October 2023

Abstract
The paper focuses on the evaluation of hailstorms’ and thunderstorms winds’ events in the United States of America, in the period from 1996 to 2022, from the marked spatio-temporal self-exciting point processes point of view. The aim of the present article is the assessment and description of the spatio-temporal spontaneous and reproducing activity of severe hailstorms’ and thunderstorms winds’ processes. Though possibly the spatio-temporal dynamics of the underlying spatio-temporal process are not exactly evaluable according to the self-exciting processes’ theoretical framework, the present application shows how the spatio-temporal pattern is well-fitted and clearly explainable, according to the flexible semi-parametric ETAS model fitting.
Alamandine: Protective Effects Against Renal Ischemia-Reperfusion Injury-Induced Renal and Liver Damage in Diabetic Rats
Authors: CENGIZ AYSE NURANSOY , OZHAN ONURAL , TANRIVERDI LOKMAN HEKIM , DOGRU FEYZI , YILDIZ AZIBE , POLAT ALAADIN , VARDI NIGAR , PARLAKPINAR HAKAN 
Published: October 2023

Abstract

Backround / Objectives: Alamandine (ALA), a heptapeptide discovered in 2013 within the renin-angiotensin system (RAS). Given the high prevalence of diabetes mellitus (DM) in society and its comorbidities, especially renal failure, which significantly impairs quality of life, this study aims to investigate the protective effects of ALA against renal ischemia-reperfusion (I/R) injury in diabetic rats.
Methods: Forty-eight 3-month-old male Sprague-Dawley rats were induced by administering a single intraperitoneal dose of 50 mcg/kg of streptozotocin (STZ). The rats were divided into four groups. Right nephrectomy was performed through dorso-lateral incisions in all rats, followed by the left renal vessels were occluded for 1 hour to induce ischemia. Reperfusion of the left kidney was initiated by removing the clamp, allowing 24 hours of reperfusion.
Results: Histopathological examination of kidney tissues revealed necrotic changes and tubular dilatation in the I/R group, which were significantly reduced in the ALA+I/R group. Immunohistochemical analysis showed increased immunoreactivity of interleukin-6 (IL-6) and caspase-3 in the I/R group, whereas the ALA+I/R group demonstrated significantly lower immunoreactivity for these markers. Liver histology showed irregular hepatocyte cords and sinusoidal dilatation in the I/R group, while the ALA+I/R group exhibited preserved classical lobular structure with reduced histopathological changes.
Conclusion: Our study demonstrates the protective effects of ALA on renal and liver tissues against damage induced by renal I/R injury in a diabetic background. Moreover, ALA exhibits protective effects against liver damage resulting from renal I/R injury.
Classification using Hyperdimensional Computing: A~Review~with~Comparative Analysis
Authors: Vergés Pere , Heddes Mike , Nunes Igor , Givargis Tony , Nicolau Alexandru 
Published: October 2023

Abstract
Hyperdimensional computing (HD), also known as vector symbolic architectures (VSA), is an emerging and promising paradigm for cognitive computing. At its core, HD/VSA is characterized by its distinctive approach to representing information using high-dimensional random vectors. The recent surge in research within this field gains momentum from its remarkable computational efficiency and ability to excel in few-shot learning scenarios. Nonetheless, the current literature is deficient in providing a comprehensive comparative analysis of various methodologies since each method uses a different benchmark to evaluate its performance. This gap obstructs the monitoring of the field's state-of-the-art advancements and acts as a significant barrier to its overall progress. To address this gap, this review not only offers a conceptual overview of the latest literature but also introduces a comprehensive comparative study of HD/VSA classification techniques. Our exploration starts with an overview of the strategies proposed to encode information as high-dimensional vectors. These vectors serve as integral components in the construction of classification models. Furthermore, we evaluate diverse classification methods as proposed in the existing literature. This evaluation encompasses techniques such as retraining and regenerative training to augment the model's performance. To conclude our study, we present a comprehensive empirical study. This study serves as an in-depth analysis, systematically comparing various HD/VSA classification approaches using two benchmarks, the first being a set of seven popular datasets used in HD/VSA and the second consisting of 121 datasets extracted from the UCI Machine Learning repository.To facilitate future research on classification with HD/VSA, we open-sourced the benchmarking and the implementations of the methods we review. Our findings yield significant insights. Firstly, encodings based on key-value pairs emerge as optimal choices, boasting superior accuracy while maintaining high efficiency. Secondly, iterative adaptive methods demonstrate remarkable efficacy, potentially complemented by a regenerative strategy depending on the specific problem. Moreover, we show how HD/VSA is able to generalize while training with a limited number of training instances. Lastly, we demonstrate the robustness of HD/VSA methodologies by subjecting the model memory to a large number of bit-flips. Our results illustrate that the model's performance remains reasonably stable until the occurrence of 40\% of bit flips, where the model's performance is drastically degraded. Overall, we have performed a thorough performance evaluation on different methods and have observed a positive trend in both evaluation and execution time.
Feasibility study of radiomics combined with CT and clinical features for early diagnosis of PTC-CLNM
Authors: 韩 露 , Hou Jie , Qin Xue , Yuan Zhongyu , Zheng Guangying , Peng Jiaxuan , Jin Hui , Gong Xiangyang 
Published: October 2023

Abstract
Background: Papillary thyroid carcinoma (PTC) is an indolent tumor, but central lymph node metastasis (CLNM) occurs at an early stage. Early diagnosis of papillary thyroid carcinoma central lymph node metastases (PTC-CLNM) is very important for patient prognosis. So, the purpose of this study is to construct a multi-dimensional early diagnosis model by combining traditional computed tomography (CT) imaging features, clinical features and radiomics features, so as to improve the early diagnosis ability of PTC-CLNM and improve the treatment effect of PTC.
Methods: A total of 226 patients with PTC who underwent head and neck or thyroid enhanced CT examinations in Zhejiang Provincial People's Hospital from January 2021 to February 2022 were included in this study. The patients were randomly divided into training set (n=180) and validation set (n=46). Imaging histologic features of individual patient were derived from pre-operative plain scan, enhancement scan arterial phase and intravenous phase images. Radiomics and multi-dimensional models were constructed using support vector machine. The properties of the multi-dimensional model were evaluated using receiver operating characteristics (ROC) on the training and test sets, and its utility for clinical purposes was assessed by Decision Curve Analysis (DCA).
Results: A total of 930 radiomics features were extracted from the three-phase CT images of each patient, from which 8 features related to CLNM were filtered. Four clinical factors (sex, age, and long and short diameters of tumors) were significantly associated with CLNM. The areas under the ROC curves for the training and validation sets in the multi-dimensional model were 0.870 (95% confidence interval [CI] = 0.818-0.921) and 0.819 (95% CI = 0.681-0.956), respectively. Decision curve analysis showed that the multidimensional model had better clinical utility than the other models.
Conclusion: The multi-dimensional radiomics model combined with traditional CT imaging features, clinical risk features and radiomics features is meaningful toward early diagnosis of Central neck node Metastasis in patients with PTC.
Surface water processes in coping with anthropogenic impact in a coastal Eastern Mediterranean region
Authors: Abboud N. , Matar Z. , Maatouk E. , Kazpard V. , Wazne M. 
Published: October 2023

Abstract
Rivers are progressively being exposed to increased anthropogenic pollution stresses that are undermining their designated-uses and affecting sensitive coastal areas. In this study, three adjacent Eastern Mediterranean coastal rivers Ibrahim, Kaleb and Beirut were evaluated. Water quality samples were collected in dry and wet season from different sampling sites along the river from the source to the outlet that represent a gradient of increased urbanization. The spatio-temporal variability of the physio-chemical properties, heavy metals (Zn, Pb, Cu, Cr and Cd) and organic matter (DOC) were statistically analyzed to better understand the contribution of point and non-point pollution sources. The three rivers (Beirut, Kaleb and Ibrahim) show a similar behavior in calcium and carbonate alkalinity due to the carbonate mineral weathering effect so they are of calcium bicarbonate type due to their calcareous geological nature. The speciation of anions was affected by temporal variation. Moreover, it is obvious that Beirut River has a different behavioral characteristic where the water is of a sulfate type water with a preferable metal-OM complexation mainly with lead, zinc and copper whereas Kaleb and Ibrahim are considered to be of a nitrate phosphate type with a preferable metal inorganic complexation specially copper that has a consistent behavior in both type of waters. This difference is attributed to the urbanization effect highly impacting Beirut River.
Identification of molecular subtypes and prognostic features of breast cancer based on TGF-β signaling-related genes
Authors: Wang Mei-Huan , Gao Yue-Hua , Qu Jia , Zhang Wei-hua 
Published: October 2023

Abstract
Purpose:The TGF-β signaling system is well understood to be involved in numerous cancer progressions, including cell invasion, epithelial-mesenchymal transition, and immunosuppression. Immune checkpoint inhibitors (ICIs) and TGF-β targeting drugs offer great promise as cancer therapies. However, the role of TGF-β in prognostic categorization and breast cancer (BC) treatment is unknown.
Methods: First, we used data from The Cancer Genome Atlas database to create a predictive model that included five TGF-signaling-related genes (TSRGs). GSE161529 dataset from the Gene Expression Omnibus collection was collected to perform single-cell analysis to further describe these TSRGs. Furthermore, based on five TSRGs, an unsupervised algorithm was used to stratify two groups of immunity and overall survival (OS) in BC patients. More research was conducted on the differences in pharmaceutical therapy and tumor microenvironment among different patient groups and clusters.
Results: The predictive model for BC contains five TSRGs: FUT8, IFNG, ID3, KLF10, and PARD6A, with single-cell analysis revealing that IFNG is primarily expressed in CD8+ T cells. Consensus clustering separated BC patients into two clusters, with cluster B having a longer OS and a better prognosis. Immunoassays revealed larger amounts of cluster B immune checkpoints and immune cells, implying that they would respond better to ICIs.
Conclusion: Our findings supports accurate prognostic classification and efficient individual care strategies for BC patients by highlighting the possible significance of TGF-β signaling pathway for BC prognosis.