bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prognostic Prediction Models for Postoperative Patients with Stage I to III Colorectal Cancer: A Retrospective Study Based on Machine Learning Methods
Authors: Ji Xiaolin , Xu Shuo , Li Xiaoyu , Xu Jinhuan , Guo Yingjie , Tian Zibin 
Published: May 2022

Abstract
Purpose To utilize the patient, tumor, and treatment features and compare the performance of machine learning algorithms, develop and validate models to predict overall, disease-free, recurrence-free, and distant metastasis-free survival, and screen important variables to improve the prognosis of patients in clinical settings.Methods More than 1000 colorectal cancer patients who underwent curative resection were grouped according to 4 endpoints and divided into testing sets and training sets (9:1). We applied 4 machine learning algorithms to predict 1-, 3-, and 5-year survival times. The area under the receiver operating characteristic curve (AUC) and average precision (AP) were our accuracy indicators. Vital parameters were screened by multivariate regression models. To achieve better prediction of longitudinal oncological outcomes, we performed 10-fold cross-validation except for the recurrence-free survival model (3-fold cross-validation). We iterated 3000 times after hyperparameter optimization and assessed the internal testing sets.Results The best AP values were greater than 80%, except for the overall survival model (69.5%). The best AUCs were all greater than 0.70 except for the recurrence free survival model (0.61). The models performed well. Variables that were widely correlated with prognoses, such as the TNM stage, were selected as important features; however, indirectly related indicators, such as Ki-67 level, were also selected.Conclusion We constructed an independent, high-accuracy "white-box" machine learning system for predicting survival times. This system may help in determining managing strategies for colorectal cancer patients and has future utility in personalized medicine and monitoring.
Jian Gan powder exerts anti-inflammatory and pro-proliferative effects and restores the dysbiosis of the gut microbiota and metabolism of the immunological liver injury mice
Authors: Li Kun , Cui Yadong , Zheng Xue , Min Chunyan , Zhang Jian , Yan Zhanpeng , Ji Yu , Zhu Fangshi 
Published: May 2022

Abstract
Background
Jian Gan powder (JGP), a traditional Chinese medicine (TCM) formula, has shown a considerable protective and therapeutic effect on hepatitis virus-induced immunological liver injury (ILI) in the clinic. However, the underlying mechanisms of the protective effects of JGP on ILI remain unknown. Evidence suggests that TCM or TCM formula can affect the intestinal microbial community and metabolic function to control liver disease progression.
Results
JGP treatment reduced inflammatory cytokine expression and promoted liver cell proliferation. The fecal 16S rRNA gene sequencing and LC-MS-based metabolomics analysis revealed that JGP could notably shape the gut microbiota structure and modify metabolic profiles. JGP treatment could restore the dysbiosis of Alloprevotella, Burkholderia-Caballeronia-Paraburkholderia, Muribaculum, Streptococcus, and Stenotrophomonas. Moreover, fecal metabolite profiles reflecting microbial activities showed that JGP modulated the disorder of biotin metabolism and steroid hormone biosynthesis in ILI mice. What’s more, the metabolites, Allylestrenol, Eplerenone, PE (P-20:0/0:0), SM d27:1, Soyasapogenol C, Chrysin, and Soyasaponin I were notably changed and remarkably reversed after JGP treatment.
Conclusion
JGP exerts anti-inflammatory and pro-proliferative effects and restores the dysbiosis of the gut microbiota and metabolism of the immunological liver injury mice. These results provided a new perspective that intestinal microbiota and their metabolites might be potential targets for elucidating the mechanism of JGP on the improvement of ILI.
Physics-Informed Deep Learning Approach for Modeling Crustal Deformation
Authors: Okazaki Tomohisa , Hirahara Kazuro , Ueda Naonori 
Published: May 2022

Abstract
The movement and deformation of the Earth's crust and upper mantle provide critical insights into the evolution of earthquake processes and future earthquake hazards. Crustal deformation can be modeled by dislocation models that represent an earthquake fault in the crust as a defect in a continuum medium. Forward and inverse modeling have been performed using various analytical methods based on Green's function for linear responses and numerical methods that discretize model regions or boundaries. In this study, we propose a novel physics-informed deep learning approach to model crustal deformation due to earthquakes. This approach obtains continuous solutions using neural networks by representing the governing equations and boundary conditions as a loss function. We use the polar coordinate system to accurately model the displacement discontinuity on a fault as a boundary condition. Neural network modeling enables flexible representation of arbitrary geometrical structures and mechanical properties of rocks, which cannot be achieved via existing methods in practice. We illustrate the validity and usefulness of this approach through example problems such as curved strike-slip faults in heterogeneous elastic media with surface topographies. Furthermore, this approach can be extended to high-dimensional, anelastic, and nonlinear problems in a straightforward manner. We anticipate that the proposed approach will be a starting point for progress in the quantitative assessment of future seismic hazards.
Cellulose-based Fluorescent Antibacterial Materials
Authors: Wang Jun , Wu Kai , Chen Cai-Hua , Chen Qiu-Yun , Liu Qing-Shan 
Published: May 2022

Abstract
The abuse of antibiotics has led to a rapid increase in the resistance of bacteria and the environmental pollution. Attenuating the bactarial membrane and metabolism by functional celluloses is an effective strategy to find bacteriostatic agents as replacers of traditional antibiotics. Herein, a novel fluorescent cellulose (CEL-THPP) was synthesized by the covalent coupling of cellulose with porphyrin derivatives (THPP). The coordination of Zn (II) ion with CEL-THPP induced the self-assembly of CEL-THPP producing CEL-THPP@Zn with near-infrared light absorption. CEL-THPP@Zn is a porous rod-like structure cellulose. CEL-THPP@Zn exhibits strong fluorescence emission at 662 nm in solid and the optical band gaps was 1.69 eV. Moreover, CEL-THPP@Zn have excellent inhibitory and adsorption effects on both Escherichia coli and Staphylococcus aureus. Therefore, this study provides a novel solution for cellulose surface modification, and the CEL-THPP@Zn can be applied to bacterial inhibition and filtration.
Finite-time non-fragile control for synchronization of fractional-order stochastic neural networks
Authors: S Kanakalakshmi , Sakthivel R , Karthick S.A , Wang Chao , Leelamani A 
Published: May 2022

Abstract
This study concerned with the synchronization problem in finite-time domain for a class of fractional-order stochastic neural networks via non-fragile controller with discontinuous activation functions. Specifically, the suggested state feedback controller sequentially cope with non-fragile scheme for gain scheduling process. Notably, the main objective of this work is to develop a non-fragile controller to obtained the finite-time synchronization criterion for the resulting synchronized error system over finite bound. For that, some consignment of sufficient conditions is derived systematically by implementing Lyapunovs indirect method and finite-time stability theory which ensures the finite-time stochastic synchronization of the stipulated neural networks. Later on, the controller gain fluctuations that obeying certain white noise sequels derived from Bernoulli distribution are formulated in terms of linear matrix inequalities. Eventually, the illustrated study are substantiated through two numerical examples and the simulation results manifest the advantage and accuracy of the proposed synchronization criteria.
New insights in the targets of action of dimethyl fumarate in endothelial cells: effects on energetic metabolism and serine synthesis
Authors: Ocaña Mª Carmen , Yang Chendong , Bernal Manuel , Martínez-Poveda Beatriz , Vu Hieu , Cárdenas Casimiro , DeBerardinis Ralph , Quesada Ana , Medina Miguel Ángel 
Published: May 2022

Abstract
Dimethyl fumarate is an ester from the Krebs cycle intermediate fumarate. This drug is approved and currently used for the treatment of psoriasis and multiple sclerosis, and its anti-angiogenic activity was reported some years ago. Due to the current clinical relevance of this compound and the recently manifested importance of endothelial cell metabolism on the angiogenic switch, we wanted to elucidate whether dimethyl fumarate has an effect on energetic metabolism of endothelial cells. Different experimental approximations were performed in endothelial cells, including proteomics, isotope tracing and metabolomics experimental approaches, in this work we studied the possible role of dimethyl fumarate in endothelial cell energetic metabolism. We demonstrate for the first time that dimethyl fumarate promotes glycolysis and diminishes cell respiration in endothelial cells, which could be a consequence of a down-regulation of serine and glycine synthesis through inhibition of PHGDH activity in these cells. Dimethyl fumarate alters the energetic metabolism of endothelial cells through an unknown mechanism, which could be the cause or the consequence of its pharmacological activity. This new discovery on the targets of this compound could open a new field of study regarding the mechanism of action of dimethyl fumarate.
Comparative evaluation of Gibbs sampler for milk yield and composition traits in Sahiwal and Tharparkar cattle
Authors: Yadav Nistha , Mukherjee Sabyasachi , Mukherjee Anupama 
Published: May 2022

Abstract
A total number of 802 and 300 records of Sahiwal and Tharparkar cows respectively were collected from history-cum-pedigree sheet for milk production and composition, animals born and reared at Livestock farm unit of ICAR-NDRI Karnal, Haryana, India. The period of study were divided into 6 periods of 5 years each (1990 to 2019). Presented analyzed data were received from selected herd for first lactation milk yield (FLMY), first lactation SNF yield (FLSNFY) and first lactation fat yield (FLFY) in both cattle breeds. Multivariate/Trivariate analyses were carried out by Bayesian approach using Gibbs sampler Animal model. Total heritability estimates for FLMY, FLSNFY and FLFY by Bayesian modeling were valued as 0.20±0.0125, 0.51±0.0114 and 0.45±0.0112 for Sahiwal and 0.46±0.0375, 0.54±0.0195 and 0.52±0.0204 for Tharparkar respectively along with its Monte Carlo Error. Direct genetic and environmental covariance between production traits were ranging from 94553 and 58851 for FLMY-FLFY to 180380 and 185780 for FLSNFY-FLFY in Sahiwal and from 116650 and 95344 for FLSNFY-FLFY to 245820 and 227400 for FLMY-FLFY in Tharparkar respectively. Comparable estimates of heritability and breeding values for ranking of sires were obtained by BLUP and Bayesian analyses from the presented data. Estimates of genetic and phenotypic (co)variance components and heritability estimates obtained using LSML which were positive but very medium to high for Sahiwal while genetic correlations were positive and high in Tharparkar. However, Gibbs Sampling (GS) is an advance and comparatively correct method of choice for many applications because of its greater robustness with comparable but slightly higher estimates of genetic parameters than LSML. The Gibbs Sampling method is flexible and dependable practice for the genetic evaluation and it can be useful in the breeding programs for highly heritable traits in Tharparkar as compared to low estimates in Sahiwal from present work.
Glow Discharge Plasma Effects on Colored Nylon 6 with Azo Dye
Authors: Yari Mohammad Reza , Zakerhamidi Mohammad Sadegh , Ghomi Hamid 
Published: May 2022

Abstract
Plasma can be used as a new low-cost and efficient method to modify polymers' surface and constituent unit configuration. This research investigates the effects of argon DC glow discharge plasma on nylon 6 polymer films doped and loaded with DR1 dye. Plasma changes the morphology and breaks some bonds, creating free radicals on the surface of the polymer and immobilizing the dye on the broken bonds. The interaction of the dye with the polymer through the broken bonds leads to an increase in the stability of the dye structure due to an increment in their resonance length. On the other hand, these interactions lead to changes in the dye's optical and geometric isomeric activity. This work studies the chemical and morphological changes of nylon 6 by plasma with AFM and spectroscopic method. Furthermore, the aging of nylon 6 films doped and loaded with DR1 dye is measured, and the polymer's color configuration changes are investigated. Plasma stabilizes the dye on the polymer surface through making changes of chemical and physical properties on the surface components.
Acetate meliorates depressive-like behaviour in a rat model of PCOS through suppression of HDAC2 expression and DNA methylation
Authors: Wolugbom John A. , Areloegbe Stephanie E. , Olaniyi Kehinde S. 
Published: May 2022

Abstract
ObjectivePolycystic Ovarian Syndrome (PCOS) is the most common endocrine disorder among women of reproductive age. PCOS has been demonstrated to induce depressive-like behaviour. Epigenetic alterations such as histone deacetylation (HDAC) and DNA methylation have been suggested in major depression. However, their effects with respect to neuroinflammation are not clear. This study therefore investigated the pathogenic role of epigenetic modification in PCOS-associated depression and the therapeutic potential of HDACi, acetate.MethodsAdult female Wistar rats (120-150 g) were allotted into groups (n = 6/group) namely: control (vehicle; p.o.), acetate-treated (200 mg/kg), letrozole (LET)-treated (1 mg/kg) and LET+Acetate-treated. Letrozole was administered for 21 days to induce PCOS.ResultsTreatment with letrozole caused hyperandrogenism, hyperinsulinemia and disrupted ovarian morphology with evidence of degenerated follicles. In addition, these animals showed depressive-like behaviours and increased expression of HDAC2 and DNA methyltransferase in PFC and hippocampal tissues. Biochemical analyses showed elevated NF-kB and acetylcholine (ACH) levels in PFC and hippocampus as well as plasma lipid peroxidation and impaired antioxidant system in LET-treated animals. Histological analysis of PFC and hippocampus showed neurodegeneration in LET-treated animals compared with control. However, these alterations were attenuated when treated with acetate.ConclusionThe study demonstrates that PCOS-associated depression is characterised by neuroinflammation and elevated ACH levels, and this is associated with increased expression of HDAC2 and DNA hypermethylation in PFC and hippocampus. Besides, the study suggests that acetate ameliorates PCOS-associated depression through the suppression of prefrontal and hippocampal DNA methyltransferase and prefrontal but not hippocampal HDAC2 expression.
Association between dietary inflammatory index and cardio-metabolic risk factors in diabetic and non-diabetic individuals: A cross-sectional study on Ravansar cohort research
Authors: Namazi Nazli , Ayati Mohammad Hossein , Anjom-Shoae Javad , Darbandi Mitra , Najafi Farid , Pasdar Yahya 
Published: May 2022

Abstract
Background: Inflammation can be involved in developing diabetes and its related complications. In the present study, the association of dietary inflammatory index (DII) and cardiometabolic risk factors in diabetic and non-diabetic individuals have been compared. Methods: In this cross-sectional study, 9039 participants from baseline data of the Ravansar Non-Communicable Disease (RaNCD) cohort; including patients with type 2 diabetes mellitus (T2DM) (n=785) and non-T2DM cases (n=8254) were included. Logistic regression analysis was conducted to determine the association between DII and main cardiometabolic risk factors in diabetic and non-diabetic populations. All analyses were performed using Stata version 14.2 software. Results: Mean age of the study population was 47.4±8.2 years and around 46% of them were men. The total mean DII score was -2.49±1.59. After adjustment for confounding factors, we found that DII can increase the risk of T2DM by 61% (95% CI:1.27 to 2.05). A comparison of the two groups also revealed that only the association of DII, obesity/overweight and dyslipidemia were significant in both diabetic and non-diabetic ones. However, no significant association was found between DII, MetS, and hypertension in either group. The association between DII and cardiovascular diseases (CVDs) was significant in only diabetic patients 1.65 (95%CI: 1.02 to 2.65) and T2DM showed an interaction with the association between DII and CVDs. Conclusions: Inflammatory potential of diet can increase the risk of T2DM. Although it can increase the risk of some cardiometabolic risk factors in both diabetic and non-diabetic cases, its effects in patients with T2DM were greater than in non-diabetic ones.
Biochemical response and RAPD DNA Profile in Lanistes carinatus from the River Nile, Aswan, Egypt as bioindicator of Heavy metals contamination
Authors: Mohamed Zeinab , Abdel-Wahab Hoda , Alnady Arwa , Younis Abuelhassan 
Published: May 2022

Abstract
Toxicity with heavy metals is the most common sort of pollution, causing harm to aquatic species, plants, and humans. In this study, lead (Pb), zinc (Zn), iron (Fe), and manganese (Mn), were studied in water, sediment, and soft tissue of Lanistes carinatus during field investigations and laboratory tests to determine contamination and toxicity. The snail was taken from two sites, site 1(near the Edfu Bridge), site 2 (Beside ferrosilicon factory), along the Nile River in Edfu, Aswan government, Egypt. We found that site 2 was more contaminated than site 1. The median lethal concentration (LC50) of 96 hours exposure for Pb, Zn, Fe and Mn on Lanistes carinatus were 12.7 mg/l, 20.6 mg/l, 95.2 mg/l, 73.6 mg/l. According to bioaccumulation factor (BWAF) data heavy metal uptake by Lanistes carinatus samples followed order Pb > Mn > Fe > Zn. This study looked at lipid peroxidation (LPO) as an oxidative stress marker, and antioxidant enzymes including superoxide dismutase (SOD), catalase (CAT), glutathione-S-transferase (GST), and glutathione peroxidase (GPx) in response to heavy metal accumulation. By comparing (LPO) activity we found that higher level of LPO activity in (Pb) treated group in site 2 than site 1, and the treated group of (Pb) had lower activity in (GPx), (GST), and (SOD)enzymes, but (CAT) enzyme was less activity in the treated group of (Zn). We investigated genetic differentiation and the impact of heavy metal pollution on the genetic structure of Lanistes carinatus using the random amplified polymorphic DNA-polymerase chain reaction (RAPD-PCR) technique.
Fine-mapping of a major QTL for protein content in BR8014887 soybean line
Authors: Bueno Rafael Delmond , Lorenzoni Rodrigo Monte , Bernardeli Arthur , Silva Luciano da Costa e , Silva Luiz Claudio Costa , Silva Jéssica Nayara Basilio , Vidigal Pedro Marcus Pereira , Piovesan Newton Deniz , Ribeiro Cleberson , Dal-Bianco Maximiller 
Published: May 2022

Abstract
Soybean is one of the main crops in the world and has great added value. Due to its importance, breeders have focused on increasing their production, leaving aside important characteristics such as grain quality. Today, the protein content in soybean seeds is lower than in previous decades, and this process needs to be adjusted to meet the requirements of the food and feed industry. The inheritance of seed traits is complex, and we are still in the infancy of this area. The elucidation of the metabolic pathways involved as well as the discovery of causal genes will be of paramount importance for the field. The main goal of the present work was to identify SNPs associated with protein content in Brazilian soybean genotypes and fine map the region associated with the protein content on chromosome 20 of the BR8014887 line to identify the possible causal gene. We identified a novel SNP (190-ss715637277) associated with protein content on BR8014887 chromosome 20 that has been shown to account for the causal effect within a region of approximately 116kb. Within the region, we have only one target gene that is annotated as a pre-mRNA splicing factor and seems to play multiple roles in the plant. The identified QTL proved to be stable, capable of increasing protein content and is considered rare. Therefore, it can be a great target for breeding programs to use and thus recover part of the protein content lost over the years.
A positive feedback loop controls Toxoplasma chronic differentiation
Authors: Licon M. , Giuliano Christopher , Chakladar Sundeep , Eberhard Julia , Shallberg Lindsey , Waldman Benjamin , Hunter Christopher , Lourido Sebastian 
Published: May 2022

Abstract
Successful infection strategies must balance pathogen amplification and persistence. In Toxoplasma gondii, this is accomplished through differentiation into dedicated cyst-forming chronic stages that avoid clearance by the host immune system. The transcription factor BFD1 is both necessary and sufficient for stage conversion; however, its regulation is not understood. We examine five factors transcriptionally activated by BFD1. One of these is a cytosolic RNA-binding protein of the CCCH-type zinc finger family, which we name BFD2. Parasites lacking BFD2 fail to induce BFD1 and are consequently unable to fully differentiate in culture or in mice. BFD2 interacts with the BFD1 transcript in a stress-dependent manner. Deletion of BFD2 reduces BFD1 protein levels, but not mRNA abundance. The reciprocal effects on BFD2 transcription and BFD1 translation outline a positive feedback loop that enforces commitment to differentiation. BFD2 helps explain how parasites commit to the chronic gene-expression program and elucidates how the balance between proliferation and persistence is achieved over the course of infection.