bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sinomenine treats rheumatoid arthritis by inhibiting MMP9 and inflammatory cytokines expression: bioinformatics analysis and experimental validation
Authors: Luo Jinfang , Zhu Yi , Yu Yang , Chen Yujie , He Kang , Liu Jianxin 
Published: June 2024

AbstractRheumatoid arthritis (RA) is a chronic systemic autoimmune disease marked by inflammatory cell infiltration and joint damage. The Chinese government has approved the prescription medication sinomenine (SIN), an effective anti-inflammation drug, for treating RA. This study evaluated the possible anti-inflammatory actions of SIN in RA based on bioinformatics analysis and experiments. Six microarray datasets were acquired from the gene expression omnibus (GEO) database. We used R software to identify differentially expressed genes (DEGs) and perform function evaluations. The CIBERSORT was used to calculate the abundance of 22 infiltrating immune cells. The weighted gene co-expression network analysis (WGCNA) was used to discover genes associated with M1 macrophages. Four public datasets were used to predict the genes of SIN. Following that, function enrichment analysis for hub genes was performed. The cytoHubba and least absolute shrinkage and selection operator (LASSO) were employed to select hub genes, and their diagnostic effectiveness was predicted using the receiver operator characteristic (ROC) curve. Molecular docking was undertaken to confirm the affinity between the SIN and hub gene. Furthermore, the therapeutic efficacy of SIN was validated in LPS-induced RAW264.7 cells line using Western blot and Enzyme-linked immunosorbent assay (ELISA). The matrix metalloproteinase 9 (MMP9) was identified as the hub M1 macrophages-related biomarker in RA using bioinformatic analysis and molecular docking. Our study indicated that MMP9 took part in IL-17 and TNF signaling pathways. Furthermore, we found that SIN suppresses the MMP9 protein overexpression and pro-inflammatory cytokines, including tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in the LPS-induced RAW264.7 cell line. In conclusion, our work sheds new light on the pathophysiology of RA and identifies MMP9 as a possible RA key gene. In conclusion, the above findings demonstrate that SIN, from an emerging research perspective, might be a potential cost-effective anti-inflammatory medication for treating RA.
Binary quantum random number generator based on value indefinite observables
Authors: Calude Cristian S. , Svozil Karl 
Published: June 2024

AbstractAll quantum random number generators based on measuring value indefinite observables are at least three-dimensional because the Kochen–Specker Theorem and the Located Kochen–Specker Theorem are false in dimension two. In this article, we construct quantum random number generators based on measuring a three-dimensional value indefinite observable that generates binary quantum random outputs with the same randomness qualities as the ternary ones: the outputs are maximally unpredictable.
The hemostatic and anti-inflammatory effects of intravenous single-dose of tranexamic acid in double-segment posterior lumbar interbody fusion: a case control study
Authors: Hao Shenshen , Luo Shiying , Zhao Zhan , Dong Shengli , Liu Shuai , Li Hongke , Li Binbin , Cao Xinhao 
Published: June 2024

AbstractThis study aims to observe the hemostatic and anti-inflammatory effects of intravenous administration of tranexamic acid (TXA) in dual segment posterior lumbar interbody fusion (PLIF). The data of 53 patients with lumbar disease treated with double-segment PLIF were included in this study. The observation group was received a single-dose intravenous of TXA (1 g/100 mL) 15 min before skin incision after general anesthesia. The control group was not received TXA. The observation indicators included postoperative activated partial prothrombin time (APTT), thrombin time (PT), thrombin time (TT), fibrinogen (FIB), platelets (PLT), and postoperative deep vein thrombosis in the lower limbs, surgical time, intraoperative bleeding volume, postoperative drainage volume, transfusion rate, postoperative hospital stay, red blood cell (RBC), hemoglobin (HB), hematocrit (HCT), C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) on the 1st, 4th, 7th, and last tested day after surgery. All patients successfully completed the operation, and there was no deep vein thrombosis after operation. There was no statistically significant difference in postoperative APTT, PT, TT, FIB, PLT, surgical time, and postoperative hospital stay between the two groups (p > 0.05). The intraoperative bleeding volume, postoperative drainage volume, and transfusion rate in the observation group were lower than those in the control group, and the differences were statistically significant (p < 0.05). There was no statistically significant difference in RBC, HB, HCT, CRP, and ESR between the two groups on the 1st, 4th, 7th, and last tested day after surgery (p > 0.05). Intravenous administration of TXA in dual segment PLIF does not affect coagulation function and can reduce bleeding volume, postoperative drainage volume, and transfusion rate. Moreover, it does not affect the postoperative inflammatory response.
Impact of copper and cobalt-based metal-organic framework materials on the performance and stability of hole-transfer layer (HTL)-free perovskite solar cells and carbon-based
Authors: Arjmand Faezeh , Rashidi Ranjbar Zohreh 
Published: June 2024

AbstractThis article investigates the impact of metal-organic frameworks (MOFs) on the performance and stability of perovskite solar cells (PSCs), specifically focusing on the type of metal and the morphology of the MOF. Two types of MOFs, copper-benzene-1,3,5-tricarboxylate (Cu-BTC MOF) with spherical morphology and cobalt-benzene-1,3,5-tricarboxylate (Co-BTC MOF) with rod morphology, are synthesized and spin-coated on TiO2 substrates to form FTO/TiO2/MOF/CH3NH3PbI3/C-paste PSCs. The morphology and size of the MOFs are characterized by scanning electron microscopy (SEM), and the crystallinity and residual PbI2 of the perovskite films are analyzed by X-ray diffraction (XRD). The results show that the Co-BTC MOF PSC exhibits the highest power conversion efficiency (PCE) of 10.4% and the best stability, retaining 82% of its initial PCE after 264 h of storage in ambient air. The improved performance and stability are attributed to the enhanced crystallinity and reduced residual PbI2 of the perovskite film after Co-BTC MOF modification. The paper showcases the immense potential of MOF-based interlayers to revolutionize PSC technology, offering a path toward next-generation solar cells with enhanced performance and longevity.
Spatiotemporal organization of ant foraging from a complex systems perspective
Authors: Cristín Javier , Fernández-López Pol , Lloret-Cabot Roger , Genovart Meritxell , Méndez Viçenc , Bartumeus Frederic , Campos Daniel 
Published: June 2024

AbstractWe use complex systems science to explore the emergent behavioral patterns that typify eusocial species, using collective ant foraging as a paradigmatic example. Our particular aim is to provide a methodology to quantify how the collective orchestration of foraging provides functional advantages to ant colonies. For this, we combine (i) a purpose-built experimental arena replicating ant foraging across realistic spatial and temporal scales, and (ii) a set of analytical tools, grounded in information theory and spin-glass approaches, to explore the resulting data. This combined approach yields computational replicas of the colonies; these are high-dimensional models that store the experimental foraging patterns through a training process, and are then able to generate statistically similar patterns, in an analogous way to machine learning tools. These in silico models are then used to explore the colony performance under different resource availability scenarios. Our findings highlight how replicas of the colonies trained under constant and predictable experimental food conditions exhibit heightened foraging efficiencies, manifested in reduced times for food discovery and gathering, and accelerated transmission of information under similar conditions. However, these same replicas demonstrate a lack of resilience when faced with new foraging conditions. Conversely, replicas of colonies trained under fluctuating and uncertain food conditions reveal lower efficiencies at specific environments but increased resilience to shifts in food location.
ECG autoencoder based on low-rank attention
Authors: Zhang Shilin , Fang Yixian , Ren Yuwei 
Published: June 2024

AbstractThe prevalence of cardiovascular disease (CVD) has surged in recent years, making it the foremost cause of mortality among humans. The Electrocardiogram (ECG), being one of the pivotal diagnostic tools for cardiovascular diseases, is increasingly gaining prominence in the field of machine learning. However, prevailing neural network models frequently disregard the spatial dimension features inherent in ECG signals. In this paper, we propose an ECG autoencoder network architecture incorporating low-rank attention (LRA-autoencoder). It is designed to capture potential spatial features of ECG signals by interpreting the signals from a spatial perspective and extracting correlations between different signal points. Additionally, the low-rank attention block (LRA-block) obtains spatial features of electrocardiogram signals through singular value decomposition, and then assigns these spatial features as weights to the electrocardiogram signals, thereby enhancing the differentiation of features among different categories. Finally, we utilize the ResNet-18 network classifier to assess the performance of the LRA-autoencoder on both the MIT-BIH Arrhythmia and PhysioNet Challenge 2017 datasets. The experimental results reveal that the proposed method demonstrates superior classification performance. The mean accuracy on the MIT-BIH Arrhythmia dataset is as high as 0.997, and the mean accuracy and $$F_1$$

F
1

-score on the PhysioNet Challenge 2017 dataset are 0.850 and 0.843.
In silico predicted compound targeting the IQGAP1-GRD domain selectively inhibits growth of human acute myeloid leukemia
Authors: Sahasrabudhe Deepak M. , Liesveld Jane L. , Minhajuddin Mohammad , Singh Niloy A. , Nath Subhangi , Kumar Vishuwes Muthu , Balys Marlene , Evans Andrew G. , Azadniv Mitra , Hansen Jeanne N. , Becker Michael W. , Sharon Ashoke , Thomas V. Kaye , Moore Richard G. , Khera Manoj K. , Jordan Craig T. , Singh Rakesh K. 
Published: June 2024

AbstractAcute myeloid leukemia (AML) is fatal in the majority of adults. Identification of new therapeutic targets and their pharmacologic modulators are needed to improve outcomes. Previous studies had shown that immunization of rabbits with normal peripheral WBCs that had been incubated with fluorodinitrobenzene elicited high titer antibodies that bound to a spectrum of human leukemias. We report that proteomic analyses of immunoaffinity-purified lysates of primary AML cells showed enrichment of scaffolding protein IQGAP1. Immunohistochemistry and gene-expression analyses confirmed IQGAP1 mRNA overexpression in various cytogenetic subtypes of primary human AML compared to normal hematopoietic cells. shRNA knockdown of IQGAP1 blocked proliferation and clonogenicity of human leukemia cell-lines. To develop small molecules targeting IQGAP1 we performed in-silico screening of 212,966 compounds, selected 4 hits targeting the IQGAP1-GRD domain, and conducted SAR of the ‘fittest hit’ to identify UR778Br, a prototypical agent targeting IQGAP1. UR778Br inhibited proliferation, induced apoptosis, resulted in G2/M arrest, and inhibited colony formation by leukemia cell-lines and primary-AML while sparing normal marrow cells. UR778Br exhibited favorable ADME/T profiles and drug-likeness to treat AML. In summary, AML shows response to IQGAP1 inhibition, and UR778Br, identified through in-silico studies, selectively targeted AML cells while sparing normal marrow.
Facile and scalable preparation of superhydrophobic brass mesh for efficient and rapid separation of oil and water
Authors: Asjadi Fatemeh , Yaghoobi Maliheh 
Published: June 2024

AbstractA facile method for preparing superhydrophobic brass mesh is proposed based on electrochemical etching and surface modification. The impact of processing time and the electric potential of the electrochemical etching were studied on the contact angle (CA) of the mesh. The samples were examined using scanning electron microscopy, Energy-dispersive X-ray spectroscopy analysis, X-ray diffraction, and Fourier-transform infrared spectroscopy. The electrochemical etching process caused the decrement of wires’ thickness and imposed roughness. Results showed more dissolution of zinc than copper under 3 V of the electric potential and the processing times of 3 and 6 min. The optimum condition of electrochemical etching was obtained under the electric voltage of 3 V for a processing time of 6 min, which led to a CA of 155.5 ± 3.2°. The thickness of the mesh wires decreased by 17.7% due to electrochemical etching in this sample. This sample also showed low adhesion for a water drop. The efficiency of oil/water separation was above 95 for the xylene and ethyl acetate in a batch system. The effect of the flow rate of the oil–water mixture on separation efficiency was also examined. The optimum flow rate was 0.8 ml s−1 with a high separation efficiency of 96.8% for xylene/oil separation.
Palaeoproteomic identification of the original binder and modern contaminants in distemper paints from Uvdal stave church, Norway
Authors: Haghighi Zahra , Mackie Meaghan , Apalnes Ørnhøi Anne , Ramsøe Abigail , Olstad Tone Marie , Armitage Simon James , Henshilwood Christopher Stuart , Cappellini Enrico 
Published: June 2024

AbstractTwo distemper paint samples taken from decorative boards in Uvdal stave church, Norway, were analysed using palaeoproteomics, with an aim of identifying their binder and possible contaminants. The results point at the use of calfskin to produce hide glue as the original paint binder, and are consistent with the instructions of binder production and resource allocation in the historical records of Norway. Although we did not observe any evidence of prior restoration treatments using protein-based materials, we found abundant traces of human saliva proteins, as well as a few oats and barley peptides, likely deposited together on the boards during their discovery in the 1970s. This work illustrates the need to fully consider contamination sources in palaeoproteomics and to inform those working with such objects about the potential for their contamination.
Convergent reductive evolution of cyanobacteria in symbiosis with Dinophysiales dinoflagellates
Authors: Nakayama Takuro , Nomura Mami , Yabuki Akinori , Shiba Kogiku , Inaba Kazuo , Inagaki Yuji 
Published: June 2024

AbstractThe diversity of marine cyanobacteria has been extensively studied due to their vital roles in ocean primary production. However, little is understood about the diversity of cyanobacterial species involved in symbiotic relationships. In this study, we successfully sequenced the complete genome of a cyanobacterium in symbiosis with Citharistes regius, a dinoflagellate species thriving in the open ocean. A phylogenomic analysis revealed that the cyanobacterium (CregCyn) belongs to the marine picocyanobacterial lineage, akin to another cyanobacterial symbiont (OmCyn) of a different dinoflagellate closely related to Citharistes. Nevertheless, these two symbionts are representing distinct lineages, suggesting independent origins of their symbiotic lifestyles. Despite the distinct origins, the genome analyses of CregCyn revealed shared characteristics with OmCyn, including an obligate symbiotic relationship with the host dinoflagellates and a degree of genome reduction. In contrast, a detailed analysis of genome subregions unveiled that the CregCyn genome carries genomic islands that are not found in the OmCyn genome. The presence of the genomic islands implies that exogenous genes have been integrated into the CregCyn genome at some point in its evolution. This study contributes to our understanding of the complex history of the symbiosis between dinoflagellates and cyanobacteria, as well as the genomic diversity of marine picocyanobacteria.
Applying an explainable machine learning model might reduce the number of negative appendectomies in pediatric patients with a high probability of acute appendicitis
Authors: Males Ivan , Boban Zvonimir , Kumric Marko , Vrdoljak Josip , Berkovic Karlotta , Pogorelic Zenon , Bozic Josko 
Published: June 2024

AbstractThe diagnosis of acute appendicitis and concurrent surgery referral is primarily based on clinical presentation, laboratory and radiological imaging. However, utilizing such an approach results in as much as 10–15% of negative appendectomies. Hence, in the present study, we aimed to develop a machine learning (ML) model designed to reduce the number of negative appendectomies in pediatric patients with a high clinical probability of acute appendicitis. The model was developed and validated on a registry of 551 pediatric patients with suspected acute appendicitis that underwent surgical treatment. Clinical, anthropometric, and laboratory features were included for model training and analysis. Three machine learning algorithms were tested (random forest, eXtreme Gradient Boosting, logistic regression) and model explainability was obtained. Random forest model provided the best predictions achieving mean specificity and sensitivity of 0.17 ± 0.01 and 0.997 ± 0.001 for detection of acute appendicitis, respectively. Furthermore, the model outperformed the appendicitis inflammatory response (AIR) score across most sensitivity–specificity combinations. Finally, the random forest model again provided the best predictions for discrimination between complicated appendicitis, and either uncomplicated acute appendicitis or no appendicitis at all, with a joint mean sensitivity of 0.994 ± 0.002 and specificity of 0.129 ± 0.009. In conclusion, the developed ML model might save as much as 17% of patients with a high clinical probability of acute appendicitis from unnecessary surgery, while missing the needed surgery in only 0.3% of cases. Additionally, it showed better diagnostic accuracy than the AIR score, as well as good accuracy in predicting complicated acute appendicitis over uncomplicated and negative cases bundled together. This may be useful in centers that advocate for the conservative treatment of uncomplicated appendicitis. Nevertheless, external validation is needed to support these findings.
RA-Net: reverse attention for generalizing residual learning
Authors: Wang Zhenyuan , Xie Xuemei , Yang Jianxiu , Song Xiaodan 
Published: June 2024

AbstractSince residual learning was proposed, identity mapping has been widely utilized in various neural networks. The method enables information transfer without any attenuation, which plays a significant role in training deeper networks. However, interference with unhindered transmission also affects the network’s performance. Accordingly, we propose a generalized residual learning architecture called reverse attention (RA), which applies high-level semantic features to supervise low-level information in the identity mapping branch. It means that higher semantic features selectively transmit low-level information to deeper layers. In addition, we propose a Modified Global Response Normalization(M-GRN) to implement reverse attention. RA-Net is derived by embedding M-GRN in the residual learning framework. The experiments show that the RA-Net brings significant improvements over residual networks on typical computer vision tasks. For classification on ImageNet-1K, compared with resnet101, RA-Net improves the Top-1 accuracy by 1.7% with comparable parameters and computational cost. For COCO detection, on Faster R-CNN, reverse attention improves box AP by 1.9%. Meanwhile, reverse attention improves UpperNet’s mIoU by 0.7% on ADE20K segmentation.
Novel technique for the ultra-sensitive detection of hazardous contaminants using an innovative sensor integrated with a bioreactor
Authors: Orzechowska Aleksandra , Czaderna-Lekka Anna , Trtílek Martin , Szymańska Renata , Trela-Makowej Agnieszka , Wątor Katarzyna 
Published: June 2024

AbstractThis study introduces an evaluation methodology tailored for bioreactors, with the aim of assessing the stress experienced by algae due to harmful contaminants released from antifouling (AF) paints. We present an online monitoring system equipped with an ultra-sensitive sensor that conducts non-invasive measurements of algal culture's optical density and physiological stage through chlorophyll fluorescence signals. By coupling the ultra-sensitive sensor with flash-induced chlorophyll fluorescence, we examined the dynamic fluorescence changes in the green microalga Chlamydomonas reinhardtii when exposed to biocides. Over a 24-h observation period, increasing concentrations of biocides led to a decrease in photosynthetic activity. Notably, a substantial reduction in the maximum quantum yield of primary photochemistry (FV/FM) was observed within the first hour of exposure. Subsequently, we detected a partial recovery in FV/FM; however, this recovery remained 50% lower than that of the controls. Integrating the advanced submersible sensor with fluorescence decay kinetics offered a comprehensive perspective on the dynamic alterations in algal cells under the exposure to biocides released from antifouling coatings. The analysis of fluorescence relaxation kinetics revealed a significant shortening of the fast and middle phases, along with an increase in the duration of the slow phase, for the coating with the highest levels of biocides. Combining automated culturing and measuring methods, this approach has demonstrated its effectiveness as an ultrasensitive and non-invasive tool for monitoring the physiology of photosynthetic cultures. This is particularly valuable in the context of studying microalgae and their early responses to various environmental conditions, as well as the potential to develop an AF system with minimal harm to the environment.
Dislocation loop and irradiation-induced synergistic-competitive mechanism in Cu-rich precipitates: a phase-field study
Authors: Yang Wenkui , Guo Qingwei , Wang Kaile , Lei Pengya , Hou Hua , Zhao Yuhong 
Published: June 2024

AbstractBoth irradiation and dislocations have been proposed as routes to rationally manipulate spatial distribution and micromorphology of precipitate. An interesting effect emerges in Fe–10at.%Cu–3at.%Mn–1.5at.%Ni–1.5at.%Al alloy due to the synergistic-competitive roles of dislocation loop and irradiation. Base on cascade mixing, vacancy-interstitial atoms and dislocation stress field model, we examine nucleation and growth dynamics of Cu-rich precipitates, where both dislocation loop and irradiation act in conjunction. Analytical treatments identify regimes, where the distribution of elements and point defects due to irradiation and dislocations are specific to the Cu-rich precipitates. Simulation results reveal that density, size and distribution of Cu-rich precipitates are a manifestation of the competing effects of the dislocation loop and the irradiation rate. More specifically, the dislocation loop preferentially assists the formation of precipitates and new dislocations at lower irradiation rates. Only the irradiation induces the formation of Cu-rich precipitates with the irradiation rate continues to increase. Equipped with molecular dynamics, where reproduces major interaction features of the solutes with point defects under displacement cascade, can verify multi-component morphologies of Cu-rich precipitates. This modeling framework provides an avenue to explore the role of dislocation loop and irradiation on the microstructural evolution of Cu-rich precipitates.