bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and validation of shared genes and key pathways in endometriosis and endometriosis-associated ovarian cancer by weighted gene co-expression network analysis and machine learning algorithms
Authors: Du Yongming , Hu Yichao , Zhang Fubin , Zhu Tianhong , Guan Yutao 
Published: February 2023

Abstract
Background: Endometriosis is a widespread disease in reproductive age. Epidemiological studies reported that patients with endometriosis had an increased risk of developing endometriosis-associated ovarian cancer (EAOC). The present study aimed to identify shared genes and key pathways that commonly interacted between EAOC and endometriosis.
Methods: The expression matrix of ovarian cancer and endometriosis were collected from the Gene Expression Omnibus database. The weighted gene co-expression network analysis (WGCNA) was used to construct co-expression gene network. Functional enrichment analyses were conducted to clarify the potential regulatory mechanisms. Protein-protein interaction (PPI) network and machine learning algorithms were applied to identify characteristic genes. CIBERSORT deconvolution algorithm was used to explore the difference in tumor immune microenvironment. Receiver operating characteristic curves were utilized to assess the clinical diagnostic ability of hub genes. Furthermore, diagnostic nomogram was constructed and evaluated for supporting clinical practicality.
Results: We identified 262 shared genes between EAOCand endometriosis via WGCNA analysis. They were mainly enriched in cytokine-cytokine receptor interaction, which may be considered a common mechanism between EAOC and endometriosis. After PPI network and machine learning algorithms, we recognized two characteristic genes (EDNRA, OCLN) and established a nomogram that presented an outstanding predictive performance. The hub genes demonstrated remarkable associations with immunological functions. OCLN were highly upregulatedin ovarian cancer compared to non-tumor tissues, while expression levels of EDNRA were significantly downregulated in ovarian cancer samples. Survival analysis indicated that dysregulated expressions of EDNRA and OCLNwere closely correlated with prognosis of ovarian cancer patients. GSEA analyses revealed that the two characteristic genes were mainly enriched in the cancer- and immune-related pathways. Gene drug interaction analysis found 15 drugs compound that interacted with the hub genes.
Conclusion: We identified two hub genes (EDNRA, OCLN) and constructed a nomogram to predict the risk of EAOC based on WGCNA analyses and machine learning algorithms. They can be used as effective predictive biomarkers for detecting EAOC. Our findings pave the way for further investigation of potential candidate genes and will aid in improving the diagnosis and treatment of EAOC in endometriosis patients.
Analysis of the acaricidal activity of Acorus gramineus extract on Dermatophagoides farinae
Authors: Wang Mei-Qing , Tang Fei-Fan , Wang Lan , Jiang Feng , Han Ren-Ren , Cao Jia-Cheng , Li Ling-Hao , Xia Yu-Ting , Wang Jing-Xuan , Zhan Xiao-Dong , Ting Liu 
Published: February 2023

Abstract
Background Mites and their excretion are considered allergens that cause allergic rhinitis, mite dermatitis, allergic asthma, and other hypersensitivity diseases in humans and animals. To study the acaricidal activity of Acorus gramineus extract on Dermatophagoides farinae, and to isolate and identify the active components.
Results Acorus gramineus extract was effective in killing Dermatophagoidesmites. The 24-hour fatality rate was 96.4% when the lowest effective concentration was 0.0625%. Six active components, A-F, were isolated and purified by silica gel column chromatography. Results showed that components D and E, identified as isoeugenol methyl ether and β-asarone, respectively, had good acaricidal effects.
Conclusion This study showed, for the first time, that isoeugenol methyl ether has significant acaricidal activity against Dermatophagoides farinae.
On the evaluation of polysaccharide–based nanofibrous membranes as suitable scaffolds for tissue engineering applications
Authors: Cienfuegos-Sarmiento A. A. , Martínez-Rodriguez M. A. , Garza-Ramos M. A. de la , García-Loera A. F. , Garza-Navarro M. A. 
Published: February 2023

Abstract
The evaluation of nanofibrous membranes based on polymeric blends of polyvinyl alcohol (PVA) and the composite carboxymethyl-cellulose/silver-nanoparticles (CMC-AgNPs) as suitable scaffolds for tissue engineering applications is reported. The nanofibrous membranes were obtained following a methodology that involves the synthesis of the CMC-AgNPs composite, preparation of aqueous polymeric blends with PVA and their electrospinning. The synthesized nanomaterials were characterized by transmission electron microscopy, scanning electron microscopy, infrared spectroscopy and uniaxial tensile assays. The antibacterial activity of the nanofibrous membranes was evaluated against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) bacteria using the direct contact test. The cell viability of the membranes was assessed using Schwann cells as model from MTT assays. The experimental evidence indicates that the mean diameter of the nanofibers decreases as the weight content of CMC-AgNPs increases. This is related with the interactions among CMC and PVA molecules, which occurs through either acetal or hydrogen bridges. The increase of CMC-AgNPs weight content also modifies the stiffness of the membranes, which results in appropriate mechanical properties for its application as tissue engineering scaffolds. Moreover, it was found that proliferation of both E. coli and S. aureus bacteria on their surface is avoided. Nonetheless, according to the cell viability assays, the membranes do not induce significant toxicity to the biological test media even after 5 days of incubation. Furthermore, they seem to provide an adequate environment for the cell proliferation, suggesting that the synthesized membranes could be applied as scaffolds for tissue engineering.
Lanthanum Oxide - Barium Oxide Nanofluid With Enhanced Thermal Engineering Application
Authors: Indulal C R , Sru S , Binoy Leo , Ravikumar R , Gani Waseem 
Published: February 2023

Abstract
Therminol is a thermally stable heat transfer fluid with a high boiling point and low vapor pressure. Boosting the heat conductivity of therminol is a potential way for increasing the efficacy of therminol-based systems. It will improve performance while compensating for the drawback of poor thermal system performance. Nanofluids are believed to be more efficient than traditional fluids. In this study, experiments were conducted to examine the thermal properties of therminol, including thermal conductivity and viscosity, when a Lanthanum Oxide-Barium Oxide (LaO-BaO) nanocomposite was dispersed in it. LaO-BaO nanocomposite was created via chemical co-precipitation route. Structural and optical characteristics of the nanosamples were investigated using X-ray diffraction (XRD) and UV-Visible Spectroscopy. Therminol was used as the base fluid in the fabrication of LaO-BaO based nanofluid. When compared to the base fluid, therminol; the nanofluid exhibits a considerable shift in heat conductivity and viscosity. To assess the potential changes in the thermal conductivity of the base fluid, thorough tests were carried out at various temperatures and weight percentages of LaO-BaO nanocomposites. The results suggest that LaO-BaO nanofluids are a superior substitute against other regular fluids in heat transfer applications.
Evaluation of aquifer characteristics and groundwater protective capacity in Abavo, Nigeria
Authors: Chinyem F. I. , Ovwamuedo G. 
Published: February 2023

Abstract
Aquifer characteristics evaluation enables the determination of aquifer’s ability to recharge as well as discharge. However, knowledge of aquifer characteristics has been scarce in Abavo area. Thus, geophysical and hydrogeological investigations, involving vertical electrical sounding (VES), pumping test and well logging were conducted in Abavo area, Nigeria, to evaluate the aquifer hydraulic properties as well as the groundwater protective capacity of the area. Seventeen (17) VES, using the Schlumberger configuration, were carried out. The field data were curve – matched, iterated, using Win Resist software. The VES result revealed subsurface lithology that comprised lateritic top soil/sand, sandy clay/clayey sand, fine sand, medium sand and coarse to gravelly sand. The VES result equally revealed an aquifer depth range from 28.8–76.6 m, with resistivity range from 1175–27,272 Ωm. Two boreholes were drilled, the cuttings were collected and were used to model the subsurface lithology. Well logging result showed that the electrical conductivity (EC) as well as total dissolved solid (TDS) are 15 µs/cm and 112 mg/l respectively, indicative of the fact that the values were within the standard organization of Nigeria (SON) permissible limit for drinking water. Pumping test analysis, using the Cooper Jacob’s method, revealed that the transmissivity, specific capacity, storativity and hydraulic conductivity are 5.9m2/day, 33.13 m/day, 0.0069 and 0.1722 m/day respectively. The study revealed longitudinal conductance and transverse resistance range of 0.001048–0.027828 Ω-1 and 105470.4–1255775.3 Ωm2 respectively. These results have established that the aquifer is semi-confined, has poor protective capacity and high rechargibility and will provide adequate, potable groundwater for local water supply to communities for domestic and other purposes.
Grape Disease Evaluation Using a Mixed-Model Ensemble of Convolution Neural Network and Random Forest
Authors: Ishengoma Farian S. , Lyimo Neema N. 
Published: February 2023

Abstract
Identifying and detecting crop diseases before they spread is a critical task for any farmer. Deep learning and computer vision are both useful for learning image features used in image classification tasks; however, deep learning takes a long time to train. In this paper, we propose an ensemble model for detecting pests on grape leaf images that employs a convolution neural network (CNN) as a feature extractor and a random forest (RF) as a classifier. CNN-based models VGG16, InceptionV3, Xception, and ResNet50 are arranged in parallel of two- and three-pathway configurations to extract more features and given to the RF for classification, and their accuracy is compared to a one-way model. Using the same data, we found that arranging CNN-based models in parallel configurations improves accuracy by 3.43% for two-pathway models and 6.37% for three-pathway models. Moreover, the best model in the one-way setting achieved 89.22% accuracy, while the best models in the two- and three-pathways settings achieved 92.65% and 95.59% accuracy, respectively.
Cyclic Hypersequent System for Transitive Closure Logic
Authors: Das Anupam , Girlando Marianna 
Published: February 2023

Abstract
We propose a cut-free cyclic system for Transitive Closure Logic (TCL) based on a form of hypersequents, suitable for automated reasoning via proof search. We show that previously proposed sequent systems are cut-free incomplete for basic validities from Kleene Algebra (KA) and Propositional Dynamic Logic (PDL), over standard translations. On the other hand, our system faithfully simulates known cyclic systems for KA and PDL, thereby inheriting their completeness results. A peculiarity of our system is its richer correctness criterion, exhibiting ‘alternating traces’ and necessitating a more intricate soundness argument than for traditional cyclic proofs.
Comparison of Schlieren-based techniques for measurements of a turbulent and wavy free surface
Authors: Bheeroo Vivek , Mandel Tracy 
Published: February 2023

Abstract
The free surface at an air-water interface can provide information regarding bathymetric complexities, as well as the subsurface flow. We present a comparison of the performance of two recent advances in light-based optical techniques for free surface measurements, Total Internal Reflection-Deflectometry and Moon-Glade Background Oriented Schlieren, with the more established method of Free-Surface Synthetic Schlieren. We make use of an optical flow algorithm over the more traditional Digital Image Correlation, in order to obtain higher spatial resolution data across the imaged free surface domain. The Optical flow algorithm presents additional benefits, such as computational efficiency and robustness in capturing large displacements and straining of tracked features. The three optical techniques are assembled in synchronization to image two free surface conditions: (1) a free surface being impinged upon by an underlying turbulent, free-shear flow and (2) a random and irregular wave field induced by a free jet. Using the high-resolution measurements, we provide insight on the emergence of multiple free surface dynamics for a turbulent free surface and dissect the local hydrodynamics of the free surface for several wave forcings. We present a comprehensive discussion on the benefits and drawbacks of each technique, including suggestions on the suitability of each technique for several experimental constraints.
Review of Delay Tolerant Networks Routing Protocols Employing Time-based Utility Measures
Authors: . Savita , Verma Ankita 
Published: February 2023

Abstract

Over the past decade, there is a pressing need for the network applications to be connected with peers in the variety of operating conditions such as unreliable networks, frequent node mobility, and resource constraints. Owing to these heterogeneous environments, the network devices face various challenges such as link disruptions, extensive propagation delays and unexpected dropping of packets. Such networks which are marked by the presence of disrupted end-to-end connections are termed as Delay Tolerant Networks (DTNs). As traditional routing protocols assume seamless connectivity, meager propagation delays and packet loss, their applicability to the delay tolerant networks are limited. Motivated to mitigate the challenges of DTNs, a plethora of routing protocols has been developed to specifically suit the extreme operating environment. The DTNs routing protocols estimate the likelihood of delivery of a message on each hop to select the most applicable relay nodes using various metrics such as frequency of contact, encounter history or duration of contact. The seminal objective of these protocols is to ensure decent reliability with less overhead in connection-disruptive and resource deficit networks. This article aims to begin with the general discussion of routing protocols which employs time-based utility measures and then diving in depth covering various aspects such as relay selection, energy requirements, message replication strategy and buffer management.
Clinical pharmacokinetics of ivermectin metabolites and their activity against Anopheles stephensi mosquitoes
Authors: Kern Charlotte , Mueller Pie , Chaccour Carlos , Liechti Matthias E , Hammann Felix , Duthaler Urs 
Published: February 2023

Abstract
Background
Ivermectin (22,23-dihydroavermectin B1a: H2B1a) is an endectocide used to treat worm infections and ectoparasites including lice and scabies mites. Furthermore, survival of malaria transmitting Anopheles mosquitoes is strongly decreased after feeding on humans recently treated with ivermectin. Currently, mass drug administration of ivermectin is under investigation as a potential novel malaria vector control tool to reduce Plasmodium transmission by mosquitoes. A “post-ivermectin effect” has also been reported, in which the survival of mosquitoes remains reduced even after ivermectin is no longer detectable in blood meals. In the present study, we analyzed existing material from human clinical trials to understand the pharmacokinetics of ivermectin metabolites and performed feeding experiments in Anopheles stephensi mosquitoes to assess whether ivermectin metabolites contribute to the mosquitocidal action of ivermectin and whether they may be responsible for the post-ivermectin effect.
Methods
Ivermectin was incubated in the presence of recombinant human cytochrome P450 3A4/5 (CYP 3A4/5) to produce ivermectin metabolites. In total, nine metabolites were purified by semi-preparative high-pressure liquid chromatography. The pharmacokinetics of the metabolites were assessed over three days in twelve healthy volunteers who received a single oral dose of 12 mg ivermectin. Blank whole blood was spiked with the isolated metabolites at levels matching the maximal blood concentration (Cmax) observed in pharmacokinetics study samples. These samples were fed to An. stephensi mosquitoes, and their survival and vitality was recorded daily over three days.
Results
Human CYP3A4 metabolized ivermectin more rapidly than CYP3A5. However, 24-hydroxy- H2B1a (M9) was solely produced by CYP3A5, whereas ivermectin metabolites M1–M8 were predominantly formed by CYP3A4. Both 3’’-O-desmethyl-H2B1a (M1) and 4-hydroxy-H2B1a (M2) killed all mosquitoes within three days post-feeding, while administration of 3’’-O-desmethyl, 4-hydroxy-H2B1a (M4) reduced survival to 35% over an observation period of three days. Ivermectin metabolites that underwent deglycosylation or hydroxylation at spiroketal moiety were not active against An. stephensi. Half-lives of M1 (54.2 ± 4.7 h) and M4 (57.5 ± 13.2 h) were considerably longer than that of the parent compound IVM (38.9 ± 20.8 h).
Conclusion
In conclusion, both metabolites contribute to the activity of ivermectin against mosquitoes and could be responsible for the “post-ivermectin effect”.
Optimal path planning and data simulation of emergency material distribution based on improved neural network algorithm
Authors: Chen Min 
Published: February 2023

Abstract
With the development of computer technology today, data storage technology is also gradually improving. Various industries can store massive amounts of data for analysis. The global climate change and the bad ecology led to frequent occurrence of natural disasters. Therefore, it has become a reality to build a system for the optimal distribution of emergency materials. The processing of big data can realize the prediction of future emergency materials storage and transportation. In this paper, the neural network model is used to calculate and the optimal emergency distribution route is analyzed according to the historical information and the data. Considering backpropagation, this paper further disposing a method to further improve the calculation of neural network algorithm. From the perspective of the structural parameters of the neural network algorithm, Using genetic algorithms to construct predictions, and combined with the actual purpose of material distribution after disasters occur. Considering the capacity constraints of distribution centers, time constraints, material needs of disaster relief points, and different means of transportation, a dual-objective path planning with multiple distribution centers and multiple disaster relief points with the shortest overall delivery time and lowest overall delivery cost is constructed. By establishing an emergency material distribution system, it can maximize the prompt and accurate delivery after a natural disaster occurs, and solves the urgent needs of the people.
Modification of suitable electrolytes for high voltage lithium-rich manganese-based cathode with wide-temperature range
Authors: Zhang Long , Dong Xi , Wang Yutong , Wang Chunxia , Cao Tiantian , Wen Jiawei , Huang Guoyong 
Published: February 2023

Abstract
New high-voltage cathode materials have been gradually developed, and their discharge voltages can reach more than 5 V ( vs. Li+/Li), but there are very few electrolytes matched with this cathode. Here, we have designed a modified electrolyte containing both FEC and LiDFOB additives which has a high oxidation potential over 5.0V, which perfectly match for high voltage lithium-rich manganese-based cathode. When FEC and LiODFB were added to the basic electrolyte, at 25℃ and 40℃，lithium-rich manganese-based cathode has excellent cycling stability in the voltage range of 2.5-5V. The capacity retention rate of the LMR/Li battery after 200 cycles was 66.5% at 25°C, and 68.7% after 100 cycles at 40°C. The first cycle discharge specific capacity of each system exceeds 200 mAh/g. In contrast, the capacity retention rate of lithium-ion batteries using primary electrolyte is merely 53.6% and 67.6% after cycling at 25 °C and 40 °C. The high-temperature, high-voltage performance exhibited by this formulation is a perfect match for Li-rich manganese-based cathode materials.
A Pancreatic Neuroendocrine carcinoma with Super High Procalcitonin mimicking Sepsis Shock: case report and literature review
Authors: Qin Ling , Li Ningning , Jia Congwei , QIN XUZHEN , Wang Xiang , Bai Chunmei 
Published: February 2023

Abstract
Besides medullary thyroid cancer, a latent and relatively mild increase of serum procalcitonin (PCT) has been found in neuroendocrine neoplasms (NENs). Here we are aiming to supply more information about NENs related PCT elevation, in order to broaden the clinical experiences about diagnosis and treatment of shock in tumor patients. we reported an advanced pancreatic neuroendocrine carcinoma (pNEC) with liver and lung metastasis, in which a rare pseudo-sepsis shock with extremely high serum PCT level (exceeding 100 ng/ml) had been demonstrated. A series of screening tests to exclude bacterial infections, including blood culture, urine culture and even metagenomic NGS (mNGS), had been performed. Given negative evidence of bacterial infection and useless broad-spectrum antibiotics treatment, steroid was used to relieve the serious inflammation and its related shock. The patient’s condition was improved and discharged. In summary, despite the ubiquitous use of PCT used in bacterial infection and sepsis shock, pNEC could cause the high level of serum PCT and even result in severe inflammation accompanied by shock. As for diagnosis and treatment strategies, pNEC should be regarded as one of rare differential diagnosis when experimental antibiotics are not working. The potential mechanism of PCT elevation and its role in prognosis of pNEC still needed to be further studied.
The role of ZEB1 in regulating Tight junctions in Antrochoanal polyp
Authors: wu yisha , Hao Dingqian , Tu Yanyi , Chen Lin , Yu Liang , Yu Peng , Chen Aiping , Wan Yuzhu , Shi Li 
Published: February 2023

Abstract
Antrochoanal polyp (ACP) is a benign nasal mass of unknown etiology. Tight junctions (TJs) are essential to the epithelial barrier that protects the body from external damage. The samples were collected from 49 controls, 37 patients with ACP and 45 patients with nasal polyp (NP). qRT-PCR and immunofluorescence staining were performed to analyze the expressions of TJs markers (ZO-1, Claudin-3 and Occludin) and ZEB1. The expression levels of TJs markers were analyzed in primary human nasal epithelial cells (hNECs) transfected with IL-17A and ZEB1 small interfering RNA (si-ZEB1). The levels of ZO-1 and Occludin mRNA were significantly downregulated in the ACP compared with the control and NP groups, and the expression of Claudin-3 was markedly lower in the ACP than control group. Immunofluorescence staining showed that the staining intensity of TJs markers was significantly decreased in the ACP and NP groups, and there was no difference between NP and ACP groups. Meanwhile, ZEB1 expression was significantly upregulated in ACP group. In hNECs, The IL-17A group showed much weaker expression of ZO-1, Claudin3 and Occludin compared to the control group.IL-17A and si-ZEB1 group reversed the down-regulation of the expression of TJs-related molecules. In addition, we observed that the degree of disruption of tight junctions correlated with the severity of the disease. The tight junctions in the ACP were extremely damaged and were correlated with the severity of the disease. In conclusion, ZEB1 was involved in the pathogenesis of ACP mediated by IL-17A though regulating tight junctions.