bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting ecosystem changes by a new model of ecosystem evolution
Authors: Yoshida Katsuhiko , Hata Kenji , Kawakami Kazuto , Hiradate Syuntaro , Osawa Takeshi , Kachi Naoki 
Published: September 2023

AbstractIn recent years, computer simulation has been increasingly used to predict changes in actual ecosystems. In these studies, snapshots of ecosystems at certain points in time were instantly constructed without considering their evolutionary histories. However, it may not be possible to correctly predict future events unless their evolutionary processes are considered. In this study, we developed a new ecosystem model for reproducing the evolutionary process on an oceanic island, targeting Nakoudojima Island of the Ogasawara Islands. This model successfully reproduced the primitive ecosystem (the entire island covered with forest) prior to the invasion of alien species. Also, by adding multiple alien species to this ecosystem, we were able to reproduce temporal changes in the ecosystem of Nakoudojima Island after invasion of alien species. Then, we performed simulations in which feral goats were eradicated, as had actually been done on the island; these suggested that after the eradication of feral goats, forests were unlikely to be restored. In the ecosystems in which forests were not restored, arboreous plants with a high growth rate colonized during the early stage of evolution. As arboreous plants with a high growth rate consume a large amount of nutrient in soil, creating an oligotrophic state. As a result, plants cannot grow, and animal species that rely on plants cannot maintain their biomass. Consequently, many animals and plants become extinct as they cannot endure disturbances by alien species, and the ecosystem loses its resilience. Therefore, even if feral goats are eradicated, forests are not restored. Thus, the founder effect from the distant past influences future ecosystem changes. Our findings show that it is useful to consider the evolutionary process of an ecosystem in predicting its future events.
Systemic epigenome-wide association study of elk treponeme-associated hoof disease
Authors: Wild Margaret A. , Taylor Kyle R. , Nilsson Eric E. , Beck Daniel , Skinner Michael K. 
Published: September 2023

AbstractTreponeme-associated hoof disease (TAHD) is an emerging disease of elk (Cervus canadensis) in the U.S. Pacific West. Because environmental epigenetics is the primary molecular process that mediates environmental factor impacts on a host organism and disease, the role of epigenetics in TAHD etiology was examined. The current study was designed to examine potential effects of TAHD on systemic epigenetic modifications in infected elk over a range of TAHD lesion severity. Leg tendons that contain predominantly fibroblast connective tissue cells were used to isolate fibroblast cells for epigenetic analysis in unaffected and TAHD-positive male and female Roosevelt and Rocky Mountain elk. Differential DNA methylation regions (DMRs) between the unaffected and TAHD-positive elk were identified for both female and male elk. The presence of TAHD was associated with alteration of the connective tissue cell epigenetics, and DMR associated genes identified. Therefore, the infected elk were found to have a systemic epigenetic alteration that was associated with the disease, despite pathology being generally limited to feet. If the elk germline epigenetics is altered then generational transmission of susceptibility to TAHD may impact subsequent generations through epigenetic inheritance. This first study of epigenetic changes associated with disease in elk suggests that TAHD promotes a systemic effect on the elk epigenetics which could exert health impacts on the elk.
Household catastrophic health expenditures for rheumatoid arthritis: a single centre study from South India
Authors: Bagepally Bhavani Shankara , Kumar S. Sajith , Sasidharan Akhil , Haridoss Madhumitha , Venkataraman Krishnamurthy 
Published: September 2023

AbstractRheumatoid arthritis (RA) not only has a physical and emotional toll but also has a substantial economic impact. This study aims to estimate the burden of catastrophic health expenditure (CHE) on households due to RA in Tamil Nadu, India. We conducted cross-sectional descriptive hospital-based single-centre study at a tertiary care private multispecialty hospital in Tamil Nadu, India. The study comprised 320 RA patients who visited the outpatient clinic from April to October 2022. Demographic and baseline descriptive characteristics were reported. Multivariable logistic regression analyses were performed to identify major determinants associated with CHE. We also examined the inequality in household annual income and CHE. Most study participants were females (88.1%) with a mean age (SD) of 55.57 ± 12.29 years. About 93% of RA patients were from urban areas, and 89.4% were literate. Only 8.1% of respondents reported having health insurance. Households experiencing CHE owing to RA were 51.4% (n = 162). The mean (95% CI) annual health expenditure for treating RA is ₹44,700 (₹41,710 to 47,690) with a median (IQR) of ₹39,210 (₹25,500) [$476 ($310)]. The corresponding mean (95% CI) and median (IQR) Out of pocket expenditure among RA patients per household were ₹40,698 (₹38,249 to 43,148) [$494 ($464 to $524)] and ₹36,450 (23,070) [$442 ($280)] respectively. Nearly half of the households with RA patients had a financial catastrophe due to healthcare costs being paid out-of-pocket and limited health insurance coverage. The results underscore the need for comprehensive approaches to strengthening public health policies along with financial risk protection and quality care in India.
Enhancing protein trapping efficiency of graphene oxide-polybutylene succinate nanofiber membrane via molecular imprinting
Authors: Sathirapongsasuti Nuankanya , Panaksri Anuchan , Jusain Benjabhorn , Boonyagul Sani , Pechprasarn Suejit , Jantanasakulwong Kittisak , Suksuwan Acharee , Thongkham Somprasong , Tanadchangsaeng Nuttapol 
Published: September 2023

AbstractFiltration of biological liquids has been widely employed in biological, medical, and environmental investigations due to its convenience; many could be performed without energy and on-site, particularly protein separation. However, most available membranes are universal protein absorption or sub-fractionation due to molecule sizes or properties. SPMA, or syringe-push membrane absorption, is a quick and easy way to prepare biofluids for protein evaluation. The idea of initiating SPMA was to filter proteins from human urine for subsequent proteomic analysis. In our previous study, we developed nanofiber membranes made from polybutylene succinate (PBS) composed of graphene oxide (GO) for SPMA. In this study, we combined molecular imprinting with our developed PBS fiber membranes mixed with graphene oxide to improve protein capture selectivity in a lock-and-key fashion and thereby increase the efficacy of protein capture. As a model, we selected albumin from human serum (ABH), a clinically significant urine biomarker, for proteomic application. The nanofibrous membrane was generated utilizing the electrospinning technique with PBS/GO composite. The PBS/GO solution mixed with ABH was injected from a syringe and transformed into nanofibers by an electric voltage, which led the fibers to a rotating collector spinning for fiber collection. The imprinting process was carried out by removing the albumin protein template from the membrane through immersion of the membrane in a 60% acetonitrile solution for 4 h to generate a molecular imprint on the membrane. Protein trapping ability, high surface area, the potential for producing affinity with proteins, and molecular-level memory were all evaluated using the fabricated membrane morphology, protein binding capacity, and quantitative protein measurement. This study revealed that GO is a controlling factor, increasing electrical conductivity and reducing fiber sizes and membrane pore areas in PBS-GO-composites. On the other hand, the molecular imprinting did not influence membrane shape, nanofiber size, or density. Human albumin imprinted membrane could increase the PBS-GO membrane’s ABH binding capacity from 50 to 83%. It can be indicated that applying the imprinting technique in combination with the graphene oxide composite technique resulted in enhanced ABH binding capabilities than using either technique individually in membrane fabrication. The suitable protein elution solution is at 60% acetonitrile with an immersion time of 4 h. Our approach has resulted in the possibility of improving filter membranes for protein enrichment and storage in a variety of biological fluids.
Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016–2022
Authors: Jung Kjær Lene , Ward Michael P. , Boklund Anette Ella , Larsen Lars Erik , Hjulsager Charlotte Kristiane , Kirkeby Carsten Thure 
Published: September 2023

AbstractAvian influenza in wild birds and poultry flocks constitutes a problem for animal welfare, food security and public health. In recent years there have been increasing numbers of outbreaks in Europe, with many poultry flocks culled after being infected with highly pathogenic avian influenza (HPAI). Continuous monitoring is crucial to enable timely implementation of control to prevent HPAI spread from wild birds to poultry and between poultry flocks within a country. We here utilize readily available public surveillance data and time-series models to predict HPAI detections within European countries and show a seasonal shift that happened during 2021–2022. The output is models capable of monitoring the weekly risk of HPAI outbreaks, to support decision making.
Amino-induced cadmium metal–organic framework based on thiazole ligand as a heterogeneous catalyst for the epoxidation of alkenes
Authors: Moghadaskhou Fatemeh , Hosseini Akram Karbalaee , Tadjarodi Azadeh , Abroudi Mehdi 
Published: September 2023

AbstractSelective epoxidation of olefins is of high interest in the chemical industry due to the many applications of epoxides. This study reports on the synthesis of Cd-MOF, [Cd(DPTTZ)(5-AIP)] (IUST-1) (where DPTTZ = 2, 5-di (pyridine-4-yl) thiazolo [5, 4-d] thiazole, 5-AIP = 5-Aminoisophthalic acid), by a reflux method, which can be considered as a fast and simple process. The morphology and structure of the synthesized IUST-1 were determined by using FE-SEM (Field Emission Scanning Electron Microscopy), EDX (Energy Dispersive Analysis of X-ray), Mapping (Elemental Mapping), CHNS (Elemental analysis), XRD (X-Ray Diffraction), FT-IR (Fourier Transform Infrared), and TGA (Thermo Gravimetric Analysis). The epoxidation of cyclooctene was investigated using the activity of catalytic IUST-1. The results showed that in the presence of tert-butyl hydroperoxide and CCl4 in a 1:2 alkene/oxidant ratio, a high epoxide yield (99.8%) was obtained. In addition, IUST-1 can be easily separated by simple filtration and recycled five times successfully with a slight decrease in activity. This compound has some advantages such as high yield, short reaction time, and ease of reuse, which make it a suitable heterogeneous catalyst for the epoxidation of cyclooctene.
A comprehensive evaluation of regional carbon emission based on the composite model in China: a case study of Huaibei city (China)
Authors: Wen Zheng , Yang Ziwei , Xing Qinfeng 
Published: September 2023

AbstractFormulating carbon emission reduction at the regional level is key to achieving the “dual carbon” strategy. A composite model is used to analyze the carbon emission reduction in Huaibei City based on the data from 2012 to 2021 and predict its change trend of carbon emission from 2022 to 2030. The study finds that: (1) the effects of observed factors on carbon emission in Huaibei City are complicated. Among them, the secondary industry has the greatest impact on carbon emission (weight is 0.32), and it is the key constraint factor of carbon emission. Population has the smallest impact on carbon emission (weight is 0.13), but its obstacle effect is significant. (2) The observed factors have a significant positive effect on the “dual carbon” strategy, but the improvement pressure is high. Among them, the conditions of all indicators have been improved except population, and it is found that each indicator can reach the level I before 2030, the “dual carbon” strategy can be achieved. This study deepens the understanding of regional carbon emission in China and the following conclusions are formed: (1) Grasping the carbon reduction effect of urbanization on the population to consolidate the new model of low-carbon development. (2) Identifying the key areas of carbon emission reduction to build a low-carbon emission oriented industrial system. (3) Strengthening the technological innovation of carbon emission reduction to achieve the strategic goal of “dual-carbon”.
Prediction of DDoS attacks in agriculture 4.0 with the help of prairie dog optimization algorithm with IDSNet
Authors: Vatambeti Ramesh , Venkatesh D. , Mamidisetti Gowtham , Damera Vijay Kumar , Manohar M. , Yadav N. Sudhakar 
Published: September 2023

AbstractIntegrating cutting-edge technology with conventional farming practices has been dubbed “smart agriculture” or “the agricultural internet of things.” Agriculture 4.0, made possible by the merging of Industry 4.0 and Intelligent Agriculture, is the next generation after industrial farming. Agriculture 4.0 introduces several additional risks, but thousands of IoT devices are left vulnerable after deployment. Security investigators are working in this area to ensure the safety of the agricultural apparatus, which may launch several DDoS attacks to render a service inaccessible and then insert bogus data to convince us that the agricultural apparatus is secure when, in fact, it has been stolen. In this paper, we provide an IDS for DDoS attacks that is built on one-dimensional convolutional neural networks (IDSNet). We employed prairie dog optimization (PDO) to fine-tune the IDSNet training settings. The proposed model's efficiency is compared to those already in use using two newly published real-world traffic datasets, CIC-DDoS attacks.
The ground state of the Kondo insulator
Authors: Karnaukhov Igor N. 
Published: September 2023

AbstractThe Kondo insulator (KI) is the state of an electron liquid in the Kondo lattice at half filling, studied within the mean field approach. We demonstrate, that the $${Z}_2$$

Z
2

-field, which is formed by interaction between electrons and local moments, leads to an insulator state in a lattice with a double cell lattice. In the ground state, electrons and local moments form singlets; in this case, no spin or charge density waves are realized in a lattice with a double cell. The Majorana-type gap spectrum of the quasi-particle excitations is realized in the $${ Z}_2$$

Z
2

-field. The gap in the spectrum decreases with increasing external magnetic field; it closes at a critical value at the insulator-metal phase transition point. In metal phase the lattice remains with a double cell. Thus, the introduction of the $${ Z}_2$$

Z
2

-field allows us to answer the key question what is the ground state of KI.
Splenic hilar lymph node dissection enhances survival in Bormann type 4 gastric cancer
Authors: Jeong Oh , Lee Han Hong , Hur Hoon , Kim Hyoung-Il 
Published: September 2023

AbstractSplenic hilar (no.10) lymph node dissection during total gastrectomy is no longer recommended for advanced proximal gastric cancer. However, the treatment efficacy of no.10 lymph node dissection in Borrmann type 4 tumors remains unclear. We enrolled 539 patients who underwent total gastrectomy for Borrmann type 4 tumors between 2006 and 2016 in four major institutions in Korea. We compared the long-term survival of the no.10 lymph node dissection (n = 309) and no-dissection groups (n = 230) using the propensity score (inverse probability of treatment weighting). The treatment effects of no.10 lymph node dissection were estimated in the weighted sample using the Cox proportional hazards regression model with a robust sandwich-type variance estimator. After inverse probability of treatment weighting, there were 540.4 patients in the no.10 lymph node dissection group and 532.7 in the no-dissection group. The two groups showed well-balanced baseline characteristics, including tumor node metastasis stage. The 5-year survival rates in the no.10 lymph node dissection and no-dissection groups were 45.7% and 38.6%, respectively (log-rank p = 0.036, hazard ratio 0.786, 95% confidence interval 0.630–0.982). Multivariate analysis revealed that no.10 lymph node dissection was an independent favorable prognostic factor (adjusted hazard ratio 0.747, 95% confidence interval 0.593–0.940) after adjusting for other prognostic factors. Sensitivity analyses in other inverse probability of treatment weighting models and the propensity score matching model showed similar results. Patients undergoing no.10 lymph node dissection showed improved survival compared to those without. No.10 lymph node dissection is recommended during total gastrectomy for patients with Borrmann type 4 gastric cancer.
Confidence-aware self-supervised learning for dense monocular depth estimation in dynamic laparoscopic scene
Authors: Hirohata Yasuhide , Sogabe Maina , Miyazaki Tetsuro , Kawase Toshihiro , Kawashima Kenji 
Published: September 2023

AbstractThis paper tackles the challenge of accurate depth estimation from monocular laparoscopic images in dynamic surgical environments. The lack of reliable ground truth due to inconsistencies within these images makes this a complex task. Further complicating the learning process is the presence of noise elements like bleeding and smoke. We propose a model learning framework that uses a generic laparoscopic surgery video dataset for training, aimed at achieving precise monocular depth estimation in dynamic surgical settings. The architecture employs binocular disparity confidence information as a self-supervisory signal, along with the disparity information from a stereo laparoscope. Our method ensures robust learning amidst outliers, influenced by tissue deformation, smoke, and surgical instruments, by utilizing a unique loss function. This function adjusts the selection and weighting of depth data for learning based on their given confidence. We trained the model using the Hamlyn Dataset and verified it with Hamlyn Dataset test data and a static dataset. The results show exceptional generalization performance and efficacy for various scene dynamics, laparoscope types, and surgical sites.
Revealing mechanism of Methazolamide for treatment of ankylosing spondylitis based on network pharmacology and GSEA
Authors: Sun Tao , Wang Manzhi , Liang Weiqiang , Gao Ping , Liu Qiang , Yan Xinfeng 
Published: September 2023

AbstractMethazolamide is a carbonic anhydrase (CA) inhibitor with satisfactory safety. Our previous studies have demonstrated the elevation of CA1 expression and the therapeutic effect of Methazolamide in Ankylosing spondylitis (AS). In this study, we explored the pathogenic role of CA1 and the pharmacological mechanism of Methazolamide in AS through Gene Set Enrichment Analysis (GSEA) and network pharmacology. Seven out of twelve CA1 related gene sets were enriched in AS group. CA1 was core enriched in above seven gene sets involving zinc ion binding, arylesterase activity and one carbon metabolic process. Functional analysis of the candidate target genes obtained from the intersection of AS associated genes and Methazolamide target genes indicated that Methazolamide exerts therapeutic effects on AS mainly through inflammatory pathways which regulate the production of tumor necrosis factor, IL-6 and nitric oxide. PTGS2, ESR1, GSK3β, JAK2, NOS2 and CA1 were selected as therapeutic targets of Methazolamide in AS. Molecular docking and molecular dynamics simulations were performed successfully. In addition, we innovatively obtained the intersection of Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and GSEA results, and found that 18 GO terms and 5 KEGG terms were indicated in the pharmacological mechanism of Methazolamide in AS, involving bone mineralization, angiogenesis, inflammation, and chemokine signaling pathways. Nevertheless, validation for these mechanisms is needed in vivo/vitro experiments.
Crosstalk tolerance analysis of coupled-line structures using least square-support vector machine technique
Authors: Alijani Mohammad G. H. , Neshati Mohammad H. 
Published: September 2023

AbstractIn this paper, crosstalk sensitivity analysis of a microwave coupled-line structure due to the fabrication imperfections is investigated using Least Square-Support Vector Machine (LS-SVM) method. Since LS-SVM uses a set of linear equations instead of a convex quadratic programming problem, the computational cost is extremely reduced compared to that of the well-known Monte Carlo (MC) analysis or even Support Vector Machine (SVM) without decreasing the accuracy. Using this method, the geometrical parameters of the coupled-line are assumed to be randomly distributed using the Latin Hypercube function and the variation range of each parameter is set to ± 50% around its central value. The frequency response of the coupled-line is estimated and compared with those of the measured and simulation ones for a few well-known practical case studies. The results show that the LS-SVM procedure quickly predicts the worst-case crosstalk expectation values and accurately anticipates the probability of obtaining various outcomes of the coupled-line for the specified parameter variation over a wide frequency range.
Bioinformatical analysis of the key differentially expressed genes for screening potential biomarkers in Wilms tumor
Authors: Cai Linghao , Shi Bo , Zhu Kun , Zhong Xiaohui , Lai Dengming , Wang Jinhu , Tou Jinfa 
Published: September 2023

AbstractWilms tumor (WT) is the most common pediatric renal malignant tumor in the world. Overall, the prognosis of Wilms tumor is very good. However, the prognosis of patients with anaplastic tumor histology or disease relapse is still poor, and their recurrence rate, metastasis rate and mortality are significantly increased compared with others. Currently, the combination of histopathological examination and molecular biology is essential to predict prognosis and guide the treatment. However, the molecular mechanism has not been well studied. Genetic profiling may be helpful in some way. Hence, we sought to identify novel promising biomarkers of WT by integrating bioinformatics analysis and to identify genes associated with the pathogenesis of WT. In the presented study, the NCBI Gene Expression Omnibus was used to download two datasets of gene expression profiles related to WT patients for the purpose of detecting overlapped differentially expressed genes (DEGs). The DEGs were then uploaded to DAVID database for enrichment analysis. In addition, the functional interactions between proteins were evaluated by simulating the protein–protein interaction (PPI) network of DEGs. The impact of selected hub genes on survival in WT patients was analyzed by using the online tool R2: Genomics Analysis and Visualization Platform. The correlation between gene expression and the degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA. Top 12 genes were identified for further study after constructing a PPI network and screening hub gene modules. Kinesin family member 2C (KIF2C) was identified as the most significant gene predicting the overall survival of WT patients. The expression of KIF2C in WT was further verified by quantitative real-time polymerase chain reaction and immunohistochemistry. Furthermore, we found that KIF2C was significantly correlated with immune cell infiltration in WT. Our present study demonstrated that altered expression of KIF2C may be involved in WT and serve as a potential prognostic biomarker for WT patients.