bluuebunny/crossref_metadata_2025_split huggingface dataset:
WITHDRAWN: Circular RNA expression in ALS is progressively deregulated and tissue-dependent
Authors: García Leticia Moreno , Moreno-Martínez Laura , Torre Miriam de la , Schoorlemmer Jon , Macías-Redondo Sofía , García-Redondo Alberto , Osta Rosario , Toivonen Janne Markus , Calvo Ana Cristina 
Published: September 2023

Abstract

There is increasing evidence on the role of circular RNAs (circRNAs) in neuronal and muscular processes. Accordingly, their dysregulation is associated with neurodegenerative diseases and myopathies. We investigated circRNA expression in the central nervous system (CNS) and skeletal muscle, the two main tissues affected in amyotrophic lateral sclerosis (ALS). Based on circRNA sequencing analysis in spinal cord from ALS mice (SOD1G93A) followed by a literature search, 30 circRNAs potentially involved in ALS were tested. All selected circRNAs were downregulated in the SOD1G93A spinal cord, whereas only half of these were quantifiable and were generally upregulated in quadriceps muscle of SOD1G93A mice. Such tissue-dependent expression pattern was observed in both sexes and circRNA abundance in the spinal cord was higher than in the muscle, both in wild-type and in SOD1G93A mice. Finally, we assessed the 18 circRNAs with the largest expression differences and the highest degree of interspecies conservation in brain samples from sporadic ALS (sALS) patients and healthy controls. Similar to the mouse model, circRNA levels tended to decrease in the CNS of sALS patients. We conclude that the expression of circRNAs may be systematically altered in the two tissues most affected by ALS in a progressive and opposed manner. Although more detailed studies are warranted, circRNAs are potentially related to ALS etiopathogenesis and could possibly serve as future biomarkers, therapeutic targets, or customized therapeutic tools to modulate the pathology.
Automatic Farmland Recognition of Remote Sensing Images Using Transfer Deep Learning
Authors: LUO GONGKUN , WANG ZHIWEN 
Published: September 2023

Abstract
Aiming at the feature extraction of farmland from remote sensing images relying on greatly manual interpretation, which consumes a lot of manpower, financial resources, and is inefficient. This paper proposes a remote sensing image farmland recognition method based on a transfer deep learning model. We also propose a simple but effective method to overcome the problems of unclear edge segmentation and partial field of view of the convolutional network. The experimental results show that the PA of the U-Net network model has reached PA 0.9124, mPA 0.7757, mIoU 0.6832, Recall 0.9586, Precision 0.94215, F1-Score 0.9503. We have obtained a competitive result and the U-Net neural network has an excellent capacity for remote sensing image farmland recognition, robustness, and practicability.
Automatic Deidentification of French Electronic Health Records: A Cost-Effective Approach Exploiting Distant Supervision and Deep Learning Models
Authors: azzouzi Mohamed El , Coatrieux Gouenou , Bellafqira Reda , Delamarre Denis , Riou Christine , Oubenali Naima , Cabon Sandie , Cuggia Marc , Bouzillé Guillaume 
Published: September 2023

Abstract
Background: Electronic health records (EHRs) contain valuable information for clinical research; however, the sensitive nature of healthcare data presents security and confidentiality challenges. Deidentification is therefore essential to protect personal data in EHRs and comply with government regulations. Named entity recognition (NER) methods have been proposed to remove personal identifiers, with deep learning-based models achieving better performance. However, manual annotation of training data is time-consuming and expensive. The aim of this study was to develop an automatic deidentification pipeline for all kinds of clinical documents based on a distant supervised method to significantly reduce the cost of manual annotations and to facilitate the transfer of the deidentification pipeline to other clinical centers.
Methods: We proposed an automated annotation process for French clinical deidentification, exploiting data from the eHOP clinical data warehouse(CDW) of the CHU de Rennes and national knowledge bases, as well as other features. In addition, this paper proposes an assisted data annotation solution using the Prodigy annotation tool. This approach aims to reduce the cost required to create a reference corpus for the evaluation of state-of-the-art NER models. Finally, we evaluated and compared the effectiveness of different NER methods.
Results: A French deidentification dataset was developed in this work, based on EHRs provided by the eHOP CDW at Rennes University Hospital, France. The dataset was rich in terms of personal information, and the distribution of entities was quite similar in the training and test datasets. We evaluated a Bi-LSTM + CRF sequence labeling architecture, combined with Flair + FastText word embeddings, on a test set of manually annotated clinical reports. The model outperformed the other tested models with a significant F1 score of 96,96%, demonstrating the effectiveness of our automatic approach for deidentifying sensitive information.
Conclusions: This study provides an automatic deidentification pipeline for clinical notes, which can facilitate the reuse of EHRs for secondary purposes such as clinical research. Our study highlights the importance of using advanced NLP techniques for effective de-identification, as well as the need for innovative solutions such as distant supervision to overcome the challenge of limited annotated data in the medical domain.
Elevated mercury exposure to bird communities inhabiting Artisanal and Small-Scale Gold Mining landscapes of the southeastern Peruvian Amazon
Authors: Pisconte Jessica Nataly , Vega Claudia Maribel , Pillaca-Ortiz Jorge Martin , Quispe Edwin , Sevillano-Ríos Cristian Steven , Tejeda Vania , Ascorra Cesar , Silman Miles R. , Fernandez Luis E. 
Published: September 2023

Abstract
Artisanal and Small-Scale Gold Mining (ASGM) represents a significant source of anthropogenic mercury release into ecosystems, with potentially severe implications for avian biodiversity. In the Madre de Dios department of the Southern Peruvian Amazon, ASGM activities have created landscapes marred by deforestation and post-mining water bodies (mining ponds) with notable methylation potential. While data on Hg contamination in terrestrial wildlife remains limited, this study measures Hg exposure in bird communities, using feathers as bioindicators. Total Hg (THg) levels in feathers from birds near water bodies, including mining ponds and oxbow lakes, were analyzed. Our results showed significantly higher Hg concentrations in birds from ASGM sites (3.14 ± 7.97 µg/g, n = 312) compared to control sites (0.47 ± 0.42 µg/g, n = 52). Factors such as trophic guilds, ASGM presence, and water body area significantly influenced feather Hg concentrations. Notably, one measurement (72.7 µg/g) exceeded known concentrations that affect reproductive success in birds and is among the highest ever reported in South America. This research quantifies Hg exposure in avian communities in Amazonian regions affected by ASGM, highlighting potential risks to regional bird populations.
Microscopic Mechanism and Evolution Model of Cracks Development in Expansive Soil under Rainfall-Evaporation Cycle
Authors: Han Liwei , Chen Ming , Ji Weibin , Si Jiaxuan , Ji Wenhui , Ma Liyuan 
Published: September 2023

Abstract
This study investigated the cracking development of expansive soils under cycling conditions of rainfall evaporation using Nuclear Magnetic Resonance(NMR) testing and image analysis methods. The study examined both internal and surface perspectives and analyzed the impact of small and medium rainfall cycles on the fine-scale mechanism of expansive soils. The experimental results showed that micropores and small-medium pores transformed into macropores during the cycling process, and this transformation was directly related to the intensity of rainfall. Furthermore, the porosity of the expansive soil increased during moisture absorption and decreased during dehumidification. Additionally, as the number of cycles increased, irreversible pores formed, resulting in the dispersion and damage of soil samples. The surface cracking development was divided into four stages, with primary cracking development occurring more rapidly during cycles of moderate rainfall evaporation. The average width of cracks was used to quantify the degradation of soil samples, and a model was developed to predict the evolution of crack width with an approximate relative error of 20% between predicted and measured values. This study has significant theoretical and practical implications for understanding the mechanisms of deformation and damage in expansive soils.
LncRNA LINC01671/YY1 positive feedback loop induced EMT modulates CCL2 secretion in colorectal cancer to attract M2-like TAM infiltration
Authors: Tan Yan , Wei Chaojie , Zhang Guqin , Ni Lan , Chen Yifei , Du Xiaohui , Zhu Minghui , Zhao Huanhuan , Cheng Zhenshun , Liu Qing 
Published: September 2023

Abstract
Background
Epithelial-mesenchymal transition (EMT) is involved in the interaction between cancer cells and tumor-associated macrophages (TAMs) in the tumor microenvironment (TME), which intimately affects tumorigenicity and metastasis. However, the potential mechanisms of EMT and the understanding of how EMT-programmed cancer cells affect TAMs recruitment and polarization remain further investigation.
Methods
The expression of LINC01671, miR-141-3p, miR-186-5p, and YY1 in CRC tissues and cells were detected by RT-qPCR. Functions of LINC01671 on cancer cell proliferation, migration, invasion and EMT were examined by a series of in vitro assays. The underlying mechanism of LINC01671 was investigated by bioinformatics analysis, RNA pull-down, luciferase reporter, RNA immunoprecipitation (RIP) and chromatin immunoprecipitation assays. A co-culture assay in vitro was used to detect the effect of LINC01671 on macrophage recruitment and polarization in TME. A xenograft mouse model was performed to explore the role of LINC01671 on tumorigenicity and TAM polarization.
Results
LncRNA LINC01671 was significantly overexpressed in colorectal cancer (CRC) tissues, and high LINC01671 level was positively correlated with poor prognosis in CRC patients. Elevated LINC01671 promoted CRC cells proliferation, migration, invasion and EMT in vitro as well as tumor growth and metastasis in vivo. Mechanistically, LINC01671 served as a sponge for miR-141-3p and miR-186-5p to facilitate YY1 expression, which in turn transcriptionally activated LINC01671 expression. Moreover, LINC01671/YY1 modulated CCL2 secretion during CRC cells EMT and subsequently favored TAMs infiltration and M2-like polarization in TME.
Conclusion
Our data demonstrate that LINC01671, identified as an oncogene, may play a crucial role in regulating YY1-mediated cancer cell EMT, thereby affecting CCL2-related M2-like TAM recruitment in CRC.
Quasi-Two-Dimensional Cs0.9Rb0.1PbBr2.1Cl0.9:PEABr Sky-Blue Light- Emitting Diodes by Potassium Bromide Doping Engineering and Interface Modification in Nickel Oxide
Authors: Chang Yi-Tsung , Zhang Lingun , Lai Mu-Jen , Liu Po-An , Chen Lung-Chien 
Published: September 2023

Abstract
This paper presents the quasi-two-dimensional (QTD) perovskite (Cs0.9Rb0.1PbBr2.1Cl0.9:PEABr) sky-blue light-emitting diode (LED) was prepared through composition engineering, doping engineering and interface modification engineering by using spin coating, it was succeed fabricated which the PEABr organic cations of large volume were introduced into three-dimensional (2D) perovskite through content proportional control, the solution of potassium bromide (KBr) was doped in the nickel oxide (NiOx) hole injection layer and the interface of the NiOx film and the perovskite film. The optimized luminance and external quantum efficiency (EQE) of the sky-blue LED with Cs0.9Rb0.1PBBr2.1Cl0.9: 80% PEABr were 989 cd/m2 and 0.68%, respectively.
The osteoprotective effect of melittin acupoint injection on CIA mice based on the gut-joint axis
Authors: Chen Fen , Liu Fenfang , Zhong Guangen , Xi Weizhe , Gao Shan , Lai Meilian , He Qiting , Zhang Jiping , Yang Le , Chen Ying , Yang Lu 
Published: September 2023

Abstract
Objective
The intestinal mucosal barrier and gut microbiota metabolism play an important role in the disease progression and treatment of rheumatoid arthritis. Melittin acupoint injection has been improved and developed from traditional bee needle therapy, and has good anti-RA efficacy. However, its potential therapeutic mechanism is still unclear. We aimed to study the effects of MAI on the efficacy, intestinal mucosal barrier, and gut microbiota metabolism of collagen induced arthritis mice.
Methods
DBA/1 mice were randomly divided into normal group, model group, methotrexate group, and melittin acupoint injection group. collagen induced arthritis mice were established using enhanced immunotherapy, and melittin acupoint injection intervention was given every 2 days for a total of 28 days of treatment. Closely observe the development of mouse arthritis, detect serum inflammatory factors using ELISA, evaluate the structure of mouse knee and intestinal tissues using histopathological staining, detect the expression of target proteins in bone and intestinal tissues using WB method, and detect differential metabolites in feces using LC-MS technology.
Results
Compared with the normal group, the arthritis index of the model group mice showed a significant upward trend after strengthened immunization; The pathological staining results of joint tissue showed proliferation of synovium, infiltration of inflammatory cells, significant formation of pannus and erosion of joint cartilage, and a significant increase in osteoclasts; Serum pro-inflammatory factors IL-1β, IL-17 and IL-23 significantly increased, while the anti-inflammatory factor TGF-β1 showed a decreasing trend. The expression of proteins related to OC differentiation was significantly increased. Pathological staining of intestinal tissue showed disruption of the intestinal mucosal barrier, significantly reduced expression of tight junction proteins, and a significant increase in serum intestinal permeability indicators DAO, D-LA, and Zonulin. Fecal metabolomics analysis showed metabolic disorders with a significant decrease in butyrate levels; Compared with the model group, the melittin acupoint injection group showed significant improvement in the above indicators, and the difference was statistically significant.
Conclusion
melittin acupoint injection had a significant therapeutic effect on Rheumatoid arthritis, improving joint inflammation and joint structural damage. Its mechanism of action may increase fecal butyric acid content by acting on fecal microbial metabolism, regulating butyric acid metabolism pathways, protecting the intestinal mucosal barrier, controlling inflammation, and thus exerting therapeutic effects on Rheumatoid arthritis.
Analysis of multipacting threshold sensitivity to the random distributions of the secondary electron yield parameters
Authors: Kazemi Firozeh , Mostajeran Maryam , Romanov Gennady 
Published: September 2023

Abstract
The way multipacting develops, depends strongly on the secondary emission property of the surface material. The knowledge of secondary electron yield is crucial for accurate prediction of the multipacting threshold. Variations in secondary electron yield parameters from experimental measurements create uncertainty, stemming from handling and surface preparation, and these uncertainties significantly affect multipacting threshold predictions. Despite their significance, the previous studies on the multipacting phenomenon did not adequately address the effect of an assumed random distribution of the secondary emission parameters on the multipacting threshold. Therefore, this paper aims to provide a comprehensive statistical study on how the different random distributions of the secondary emission parameters and, as a result, the uncertainty in the secondary electron yield affect multipacting thresholds. We focus on three commonly used distributions, namely uniform, normal, and truncated normal distributions, to define the uncertainty of random inputs. We use the chaos polynomial expansion method to determine how much each of the random parameters contributes to the multipacting threshold uncertainty. Additionally, we calculate Sobol sensitivity indices to evaluate the impact of the individual parameters or groups of parameters on the model outputs and study how different random distributions of these parameters affected the Sobol index results.
Improving Alkaline Stress Tolerance in Maize through Seed Priming with Silicon Nanoparticles: A Comprehensive Investigation of Growth, Photosynthetic Pigments, Antioxidants, and Ion Balance
Authors: Alsamadany Hameed , Alharby Hesham F. , Ahmad Zahoor , Al-Zahrani Hassan S. , Alzahrani Yahya M. , Almaghamsi Afaf 
Published: September 2023

Abstract
Silicon nanoparticles (Si NPs) have long been acknowledged for their ability to enhance plant defense against various biotic and abiotic stresses. Maize (Zea mays L.), among the plants known to accumulate Si NPs, is particularly vulnerable to alkaline stress. This study aimed to investigate the effects of different concentrations of Na2CO3 (0 and 75 mM) on maize seeds, along with varying levels of silicon nanoparticles (Si NPs) 0, 1.5 mM, and 3 mM over a 25-day period. The alkaline stress significantly impaired growth parameters, leaf relative water content (LRWC), and the concentrations of photosynthetic pigments, soluble sugars, total phenols, and potassium ions (K+), as well as the potassium/sodium ion (K+/Na+) ratio. However, this stress led to increased levels of soluble proteins, total free amino acids, proline, and sodium ions (Na+), and also elevated the activities of antioxidant enzymes superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) in the stressed plants. Conversely, applying silicon nanoparticles through seed-priming mitigated the growth impediments in stressed plants. This intervention resulted in improved LRWC, higher levels of photosynthetic pigments, soluble sugars, soluble proteins, total free amino acids, and potassium ions (K+). Moreover, Si NPs enhanced the activities of SOD, CAT, and POD enzymes. Si supplementation also led to decreased levels of proline and sodium ions (Na+), which in turn facilitated a more favorable adjustment of the K+/Na+ ratio in stressed plants.
Residual Mechanical Properties of Post Fire Steel Rebars
Authors: Eranki Bhargavi , Durga S. Kanaka , malasani potharaju , Eranki Bhargavi 
Published: September 2023

Abstract
Reinforcement steel is a crucial material for buildings utilized extensively in composite construction due to its benefits, including strength, durability and simplicity of availability. One of the major risks that seriously harms a structure and eventually causes it to collapse is fire. The reinforcing steel significantly loses both its intrinsic mechanical qualities and service life as a result of the intensity of fire exposure. The present research work is being conducted to investigate the residual strength of yield, tensile strength and elongation percentage of 16mmᴓ post fire steel reinforcement bars. The sample specimens were collected from failed post fire RC columns from previous experimental work which were exposed to 300,500 and 800oC temperature for 2.0 hour fire duration having 20, 30 and 40mm concrete covers. The impact of temperature and cover of concrete on mechanical characteristics of post fire steel reinforcement is also discussed.
Psychosocial experiences of pregnant women living with HIV in Ibadan, Oyo State
Authors: Akinsolu Folahanmi , Lawale Abisola , Bankole Samuel , Adegbite Zaniab , Adewole Ifeoluwa , Abodunrin Olunike , Olagunju Mobolaji , Ola Oluwabukola , Chukwuemeka Abel , Gambari Aisha , Salako Abideen , Ezechi Oliver 
Published: September 2023

Abstract
Introduction: Pregnancy often intensifies psychological vulnerabilities in women living with HIV (WLHIV) due to increased stressors such as health concerns, infant infection risks, and the management of special neonatal needs like prophylactic antiretroviral care.
Methodology: The study was conducted in four HIV treatment centres with participant selection based on the following criteria: an Edinburgh Postnatal Depression Scale (EPDS) score of 13 or above, gestational age between 14 to 40 weeks, less than five years of antiretroviral therapy (ART) usage, and history of partner conflict. This research forms a more extensive study of stress and depression amongst pregnant and postpartum WLWH. In-depth interviews, ranging from 20 to 40 minutes, were conducted with 26 HIV-positive pregnant women in private rooms within selected antiretroviral clinics from October and December 2022.
Results and Discussion: The study discovered that the support received from healthcare providers concerning ART and Prevention of Mother-To-Child Transmission (PMTCT) practices alleviated women's fear of death and perinatal transmission which bolstered their involvement in HIV care and fostered the birth of children not infected with HIV. Women perceived monogamy as a protective measure against HIV contraction. Participants who reported having partners engaging in unsafe sexual practices expressed anger and blame. The observation of other women with similar experiences aided in coping mechanisms, reaffirming previous findings that knowing someone living with HIV helps to accept their status due to the comfort derived from shared experiences.
Conclusion: Healthcare providers attending to pregnant WLWH can alleviate psychological distress by reinforcing positive coping strategies. These include consistent psychological distress screenings in HIV clinics and relevant mental health evaluations with appropriate care referrals.
Blockchain-Assisted Cross-silo Graph Federated Learning for Network Intrusion Detection
Authors: Shen Hang , Zhou Yanjing , Wang Tianjing , Zhang Yu , Bai Guangwei , Miao Xiaodong 
Published: September 2023

Abstract
In this paper, a blockchain-assisted cross-silo graph federated learning (B-CGFL) framework is presented for large-scale network intrusion detection, aiming to break down barriers among different organizations and achieve a secure and transparent multi-party collaboration ecosystem. The network scenario is divided into multiple regions. Organizations in each region leverage graph neural networks to analyze local network flow topology information and identify traffic types accurately. With cross-silo graph federated learning, coordinators and organizations collaboratively complete the training and updating of global intrusion detection models. Multiple coordinators jointly maintain a chain to improve the global model’s scalability and storage security. Oracle nodes bridge the off-chain data provider and on-chain smart contracts, enabling secure transmission in off-chain model accuracy testing. For fair competition, a reputation-aware model incentive mechanism is designed to improve global model quality. Security analysis confirms that B-CGFL can defend against inference attacks, model plagiarism, and tampering with model test results. Experiments on three challenging datasets ToN-IoT, CSE-CIC-IDS2018, and BoT-IoT demonstrate that compared with benchmark machine learning methods, B-CGFL exhibits superior performance in accuracy and F1-score and facilitates model quality improvement.