bluuebunny/crossref_metadata_2025_split huggingface dataset:
Upregulation of CXCL1 and FCGR1A is Associated With the ischemic stroke and Crohn’s Disease
Authors: Zhang wenjing , Li Ying , Xu Haoqun , Li Chong , Zhang Yimin , Han Bingbing 
Published: March 2023

Abstract
Background
Evidence is accumulating that brain disorders increase risk of gut diseases, and that there is a causal connection between ischemic stroke (IS) and Crohn's disease (CD). It is unclear what mechanisms underlie the coexistence of IS and CD. This study was designed to obtain insights into the mechanisms mediating the coexistence of IS and CD based on a quantitative analysis of a public RNA sequencing database.
Methods
Gene Expression Omnibus (GEO) databases were used to download IS (GSE58294) and CD (GSE95095). To explore the functions of different genes (DEGs), the edgeR and limma packages of R were used. Gene Ontology and Kyoto Encyclopedia analyses of common DEGs were also conducted. A genetic interaction database was established by using protein–protein interaction (PPI) networks. After visualization by cytoscape, hub genes were screened out by plug-in. Then, Hub gene validations were performed in GSE16561 and GSE36807 for IS and CD, respectively. To evaluate the predictive value of hub genes, ROC curves were used. Finally, genome enrichment and immune infiltration were used to analyze hub genes.
Results
The 108 common DEGs were classified into 12 downregulated and 96 upregulated. A functional analysis revealed that inflammation and the immune pathway were critical for the initiation and development of IS and CD. Validation revealed that all areas under the curve for IS and CD were generally greater than 0.7 and that the hub genes CXCL1 and FCGR1A had good diagnostic markers for both diseases. There was a positive correlation between neutrophil infiltration and hub genes. The path of immune processes was associated with high expression of CXCL1 and FCGR1A in both IS and CD following neutrophil infiltration.
Conclusions
Our study performed a series of analyses of DEGs common to IS and CD, with the aim of revealing their common pathogenesis. Both diseases could benefit from analysis of these common pathways and hub genes for the identification of potential biomarkers, helping valuable therapeutic clues.
Immediate implant placement influenced by musical flow: A prospective randomized controlled clinical trial
Authors: Ángel L.A. Esteban Pellicer Lorenzo , Luis J.L. Martínez Rubio Jose , Elisabeth E. Casañas Gil , Jesús A.J. Conde Villar Antonio 
Published: March 2023

Abstract
Objetives
The purpose of this study was to test how musical flow using baroque (BM) and classical era music (CM) as a non-pharmacological therapy can control anxiety and pain levels among patients undergoing IPI (Immediate post-extraction implants).
Material and Methods
78 patients who required an IPI were enrolled in this randomized clinical trial. Each patient was assigned to one of the three experimental groups with a simple randomization: Group I (n=26) listened to BM; Group II (n=27) listened to CM; and Group III (n=25) did not listen to music and was the control group (C). The physiological dependent variables analyzed were SBP, DBP, HR and SpO2. The psychological dependent variable analyzed was MDAS and VAS, measured before and after surgery. In all cases, the level of statistical significance was set at p < 0.01.
Results
Statistically significant differences were found in the SBP decrease in the CM group (p=.001, CI=1.9716-6.5840) and the BM group (p=.003, CI=1.4450-6.4396). Anxiety levels during the intervention decreased in both groups that listened to music: BM group (p=.002, CI=.645-2.662) and CM group (p=.000, CI=1.523-3.884).
Conclusion
Patients undergoing IPI placement surgery can register lower levels of SPB when listening to BM and CM, improving their anxiety levels.
Clinical relevance
The evidence on the effect of music as a non-pharmacological tool in reducing anxiety during dental implant surgery is very scarce. Only two randomized clinical trials have been previously published (Gülnahar & Kupeli, 2020 and Esteban Pellicer et al., 2022). The present study is the first to be published on immediate post-extraction implants.
Trial Registration Number:
NCT05052034
https://beta.clinicaltrials.gov/study/NCT05052034?distance=50&cond=%20NCT05052034&rank=1
Effects of Perioperative Lidocaine Infusion on Pain Management and Quality of Recovery Following Thyroid Surgery: A Systematic Review and Meta-analysis
Authors: Wu Yan , Tang Xihui , Xu Yuqing , Chen Qingsong , Liu Su 
Published: March 2023

Abstract
Background
Thyroid surgery is often considered minor, and the postoperative pain is usually ignored. However, according to previous researches, the pain after thyroid surgery ranged from moderate to severe. Poorly controlled pain may lead to a series of adverse events, including dissatisfaction of patients, bad recovery, and extended hospital stay. Intravenous infusion of lidocaine has been proven to be effective in relieving pain after cholecystectomy, spinal surgery, and colorectal surgery. This meta-analysis was designed to explore the effects of lidocaine infusion on pain management and quality of recovery after thyroid surgery.
Methods
We conducted a comprehensive search of the Cochrane Library, PUBMED, Web of Science, EMBASE, China National Knowledge Infrastructure (CNKI), Wanfang, VIP, and China Biomedical Literature Database (CBM) from inception to September 12, 2022. Based on our previously established inclusion and exclusion criteria, eligible studies were involved. The primary outcomes were postsurgical pain scores and quality of recovery. The secondary outcomes included opioids consumption, hemodynamics variables, time to awareness and extubation, and adverse events. All analyses were performed using the random effects model with RevMan 5.4 software. We also evaluated the evidence quality of results by GRADEprofiler 3.6.
Results
A sum of 11 RCTs with 761 patients were involved. Compared to the controlled group, lidocaine reduced pain scores at 2h, 4h, 8h, and 12h after surgery, but not at 24h and 48h. Besides, lidocaine also facilitated recovery (mean difference [MD] = 7, 95% CI [4.78–9.25], P = 0.40, I2 = 0%), reduced opioids consumption during surgery (MD=-5.61, 95% CI [-7.90, -3.31], P = 0.97, I2 = 0%), and lowered the incidence of cough during extubation (RR = 0.41, 95% CI [0.30, 0.56], P = 0.34, I2 = 10%). No lidocaine-related adverse events was found in our meta-analysis.
Conclusions
Perioperative infusions of lidocaine could alleviate postoperative pain and facilitate recovery on the first day after surgery, without causing adverse events. Considering the high heterogeneity and relatively low quality of evidence among most of the results, further validation is reasonable.
Retrospective Validation Study of an Artificial Neural Network-Based Preoperative Decision-Support Tool for Noninvasive Lymph Node Staging (NILS) in Women with Primary Breast Cancer (ISRCTN14341750)
Authors: Skarping Ida , Ellbrant Julia , Dihge Looket , Ohlsson Mattias , Huss Linnea , Bendahl Pär-Ola , Rydén Lisa 
Published: March 2023

Abstract
Background

Surgical sentinel lymph node biopsy (SLNB) is routinely used to reliably stage axillary lymph nodes in early breast cancer (BC). However, SLNB may be associated with postoperative arm morbidities. For most patients with BC undergoing SLNB, the findings are benign, and the procedure is currently questioned. A decision-support tool for the prediction of benign sentinel lymph nodes based on preoperatively available data has been developed using artificial neural network modelling.

Methods

This was a retrospective geographical and temporal validation study of the noninvasive lymph node staging (NILS) model, based on preoperatively available data from 586 women consecutively diagnosed with primary BC at two sites. Ten preoperative clinicopathological characteristics from each patient were entered into the web-based calculator, and the probability of benign lymph nodes was predicted. The performance of the NILS model was assessed in terms of discrimination with the area under the receiver operating characteristic curve (AUC) and calibration, that is, comparison of the observed and predicted event rates of benign axillary nodal status (N0) using calibration slope and intercept. The primary endpoint was axillary nodal status (discrimination, benign [N0] vs. metastatic axillary nodal status [N+]) determined by the NILS model compared to nodal status by definitive pathology.

Results

The mean age of the women in the cohort was 65 years, and most of them (93%) had luminal cancers. Approximately three-fourths of the patients had no metastases in SLNB (N0 74% and 73%, respectively). The AUC for the predicted probabilities for the whole cohort was 0.6741 (95% confidence interval: 0.6255–0.7227). More than one in four patients (n=151, 26%) were identified as candidates for SLNB omission when applying the predefined cut-off for lymph node negativity from the development cohort. The NILS model showed the best calibration in patients with a predicted high probability of healthy axilla.

Conclusion

The performance of the NILS model was satisfactory. In approximately every fourth patient, SLNB could potentially be omitted. Considering the shift from postoperatively to preoperatively available predictors in this validation study, we have demonstrated the robustness of the NILS model. The clinical usability of the web interface will be evaluated before its clinical implementation.

Trial registration

Registered in the ISRCTN registry with study ID ISRCTN14341750.
Date of registration 23/11/2018.
Big Data Storage based on CAN Protocol
Authors: KABRE Lacine , TIENDREBEOGO Telesphore 
Published: March 2023

Abstract
Big Data refers to huge amounts of heterogeneous data from various traditional and new data sources. This data is constantly changing. However, due to their great heterogeneity, several architectural approaches are proposed to centrally process and analyze the huge amounts of data. A Big Data architecture describes the blueprint of a system that processes a huge amount of data from its storage, processing, analysis and visualization. From one architecture to another, there are advantages and limitations especially in terms of time and processing mode. In our paper, we propose a decentralized architecture based on the peer-to-peer protocol CAN (Content Adressable Network) using image properties associated with SHA-512 keys to secure the data. First, we evaluated the existing Big Data technologies from the architecture to the data storage model. Then, we presented all the conceptual aspects of our architecture and we ended with the evaluation of a symbolic version developed and deployed in a local network.
The effect of Mesenchymal stem cells- derived exosomes on the expression of MAGEA6 and MAGEA11 in a human colorectal carcinoma cell line
Authors: Azimi Maryam , Aghamajidi Azin , Khosroshahi Leila Mohamed , Bahramkiya Sara , Mansourabadi Amir Hossein 
Published: March 2023

Abstract
Background: Melanoma Antigen Gene (MAGE) proteins belong to a large, highly conserved family of proteins with a common homology domain. Most MAGE proteins are expressed exclusively in reproductive tissues, but they are aberrantly expressed in many types of cancer. In this study, we aimed to investigate the effects of adipose-derived mesenchymal stem cells secreted exosomes on the expression of MAGEA6 and MAGEA11 genes in the HCT-116 tumor cell line.
Materials and Methods: Ad-MSCs were assessed for their surface antigenic profile using specific markers. TEM and western blot were used to evaluate the quality of the isolated exosomes, which were purified from the Ad-MSc supernatant. HCT-116 cells were co-cultured with MSC-conditioned medium (MSC-CM) and/or with 100 ug/ml of MSC-derived exosomes for 48h. Real-time PCR was carried out to determine the expression of MAGEA6 and MAGEA11 in HCT-116. Relative expression levels were calculated using the 2-ΔΔct method.
Results: Our result showed that MAGEA11 mRNA expression levels were significantly reduced in exosome (EXO) and/or CM (MSC- conditioned medium) +EXO treated HCT116 while MAGEA6 mRNA expression levels were significantly reduced in CM+EXO treated HCT116 (P-value < 0.05).
Conclusion: The current study showed that MSC-derived exosomes could inhibit the expression of two important molecules involved in tumor progression. Hence it seems MSCs-derived exosomes may hold a hopeful future as drug delivery vehicles that need further investigation.
Performance of water-based printed hybrid graphene/silver nanoparticles conductive inks for flexible strain sensor applications
Authors: Htwe Y. Z.N. , Mariatti M. 
Published: March 2023

Abstract
Flexible electronic devices such as wearable strain sensors have drawn a lot of interest in health monitoring systems. In the present study, hybrid ink printed flexible strain sensors made of graphene and silver nanoparticles (AgNPs) was formulated. The main aim of the study is to investigate effect of hybrid graphene and AgNPs ratios on the properties of conductive inks and their performance as flexible strain sensors. The new conductive inks were printed on various types flexible substrates; polyethylene terephthalate (PET), polyimide (PI), and polyvinyl alcohol (PVA). The performance of conductive ink on these substrates were evaluated. Results showed that ratio of graphene/AgNPs influence the properties of conductive inks. Graphene/AgNPs with a 0.3/0.2 wt% exhibit higher stability, wettability, and electrical conductivity than those 0.4/0.1, 0.2/0.3, and 0.1/0.4 wt%. Hybrid Graphene/AgNPs conductive ink printed on PI substrate showed better wettability and electrical performance compared to those on PET and PVA substrates. The gauge factor (GF) of PI substrate is higher 6.2% and 32% compared to PET and PVA at the 30% strain range, respectively. In short, the hybrid graphene/AgNPs strain sensor on PI that showed good linearity, sensitivity, and stability has a high potential to be used in low-strain health monitoring systems.
Phytotoxicity of chromium (III and VI) on tomato (Lycopersicum esculentum L.) grown in sand culture
Authors: Srivast Saumya 
Published: March 2023

Abstract
Chromium (Cr), an element naturally occurring in earth’s crust, and a known toxic heavy metal, causes deleterious effects on plants when present in excessive amounts. The present study is aimed to evaluate the effects of both trivalent and hexavalent Cr separately on tomato plants. For this, a sand culture glasshouse experiment was conducted with 0.1 mM Cr3+, 0.2 mM Cr3+, 0.1 mM Cr6+, 0.2 mM Cr6+ doses to access the Cr accumulation pattern and study its effects on growth, morphology, photosynthetic pigments, nutrient status and oxidative stress parameters in tomato. Chromium toxicity resulted in growth depression and reduction in chlorophyll content of plants. Cr caused wilting and necrosis of especially old leaves. Cr was mainly found to be accumulated in roots, and also caused hindrance in the translocation of micronutrients to upper parts of the plants. Cr toxicity caused oxidative stress which was reflected in the form of increased levels of lipid peroxidation and anti oxidative enzymes. Plants did not bear any fruits at 0.2 mM Cr3+ and 0.2 mM Cr6+ treatments. Among both forms of Cr (3+ and 6+) tested, Cr6+ clearly proved to be more toxic for growth and metabolism of plants. However, at many places, 0.2 mM Cr3+ showed more toxicity than 0.1 mM Cr6+ stating that higher doses of Cr3+ are also very harmful to tomato plants.
News Headlines Classification for Disease Outbreak Detection using Modified Term Weighting approach
Authors: Joy Manju , Krishnaveni M 
Published: March 2023

Abstract

The Covid-19 pandemic exposed weaknesses in healthcare systems in the world and revealed the importance of efficient Bio surveillance systems that can monitor disease outbreaks on a real-time basis. Event-based health surveillance systems are popular due to their ability to utilize health information from internet sources such as digital newspapers and social networking sites for early detection of outbreaks. Studies claim that all deadly outbreaks declared by WHO are first detected through these informal online sources. Unfortunately, existing systems are not providing actionable data for outbreak prevention. Action plans for handling outbreaks can be developed only if regional-specific data is available. The proposed study is intended to detect local or regional level outbreaks happening in the health domain of Kerala, in particular, by automatic extraction and examination of internet media reports covering Kerala news. In this paper, various methods for retrieving outbreak news from news portals are studied and a novel method is proposed for retrieving disease-related news items using ML techniques by implementing various text classification algorithms. Implementation of a modified term weighting approach to augment classification accuracy is a major contribution of the proposed work. Traditional TF-IDF term weighting algorithm do not consider the significance of a term in a particular domain. The Random Forest classifier gave maximum accuracy of 94.48% by the TF-IDF approach which improved to 100% by our modified term weighting scheme where the significance of the term with respect to a particular domain is also considered while determining the weight of the term during vectorization.
The Effectiveness of Feature Extraction and Machine Learning based approach for Early Detection of Oral Cancer
Authors: Kumari Alka , Mehta Ashok Kumar 
Published: March 2023

Abstract
The early-stage detection of cancer disease is helpful for medical practitioners by reducing the diagnosis time in its treatment. The motivation behind this undertaking is to review the most recent Feature extraction (Fe) and classification methods for detecting Oral Cancer (OC) in various image formats that have recently been reviewed and published. The review gives out that the early and accurate detection of OC disease is still a challenge for the healthcare industry. With the assistance of this survey, we proposed a Machine learning (Ml)-based procedure along with multistage Fe for OC detection in different locations of mouth through normal oral images. This proposed work is using different techniques for the classification of disease where histogram oriented gradients (hog) used for preprocessing and Principal component analysis (Pca) and Gray level co-occurrence matrix(Glcm) are used for Fe and different Ml algorithms were utilized for OC classification. The tests used 131 images from a real human oral imaging dataset, 44 of which were normal and 87 of which were aberrant.
The classification accuracy for the Support vector machine(Svm) was 80.95% on test images, which was quite impressive. Additionally, a comparison of the suggested method with other recently published Ml methods shows the effectiveness of the proposed technique. The outcomes showed that the suggested hybrid strategy is precise, quick, and reliable. The results showed how effective the suggested algorithm was. Finally, alternative directions for the future are given. A flowchart is used to present the proposed process in order to facilitate the understanding of the work.
Personal care products related phenols and parabens in relation to urinary incontinence in the US population
Authors: Jiang Jinjiang , Chen Bo , Tang Bo , Li Jinze , Tan Daqing , Wei Qiang 
Published: March 2023

Abstract
Our research aims to assess the association of personal care products (PCPs) related parabens(PBs) and phenols(PNs) including Triclosan(TCS), Bisphenol A(BPA), Benzophenone-3(BP-3), Butylparaben(BPB), Ethylparaben(EPB), Methylparaben(MPB) and Propylparaben(PPB) detected in urine samples with urinary incontinence in the US population. A cross-sectional analysis was conducted based on the data from the National Health and Nutrition Examination Survey (Nhanes) 2007-2016. A total of 7,690 participants diagnosed by self-reported questionnaires were included in the final analysis. Of theseparticipants, 12.80% reported SUI, 11.80% reported UUI and 10.22% reported MUI. In the fully adjusted multivariable models, BP-3 exposure showed a positive association with SUI (OR 1.07 95% CI1.02-1.14 p=0.045), BPA exposure increased the risk of UUI (OR 1.21 95% CI1.01-1.44 p=0.046) and MUI (OR 1.26 95% CI 1.02-1.54 p=0.029). Furthermore, TCS was found related to a decreased incidence of MUI (OR 0.87 95%CI 0.79-0.97 p=0.009). No significant correlation was found between parabens and urinary incontinence. Among the female population, our research revealed that BPA exposure increased the risk of MUI (OR 1.28 95% CI 1.01-1.63 p=0.043) when covariables such as vaginal deliveries, hysterectomy, and hormone use history were included. The maximal tertile of BP-3 showed a higher likelihood of SUI and MUI among participants compared with the lowest tertile. All in all, exposure to BPA, TCS, and BP-3 may engaged in the development of urine incontinence in various ways.
Convolutional neural networks improved HRV analysis accuracy by single-lead Holter
Authors: Tang Chunping , Huang Qiong , Shen Qin , Zhou Qianzheng , Kong Xiangqing , Zhou Ningtian 
Published: March 2023

Abstract
Background
New artificial intelligence (AI) algorithms are being applied to HRV but there is still needed for more comparison with classical HRV metrics. Convolutional Neural Network (CNN) was used to analyze HRV in four different groups distinguished by body mass index (BMI) and age.
Methods
Total 265 patients wore an AI single-lead Holter and traditional multi-lead Holter for less than 22 h. Indeed, RR-interval sequence as input for the CNN, then linear fitting and Bland–Altman analysis were used to illustrate the statistical results of AI Holter and traditional Holter in four groups: BMI < 24 kg/m2 and age < 65 years, BMI < 24 kg/m2 and age ≥ 65 years, BMI ≥ 24 kg/m2 and age < 65 years, and BMI ≥ 24 kg/m2 and age ≥ 65 years.
Results
All groups had acceptable biases and r-values for different HRV parameters. SDANN was the most accurate HRV parameter in all groups, and SDNN, PNN50 also showed better test efficiency in specific groups.
Conclusions
The AI single-lead Holter was reliable for HRV detection, and SDNN showed a satisfactory accuracy in all groups, but SDANN and PNN50 showed better test efficiency in specific groups.
A Non-invasive Optimized System for rapid detection of Gilomas Brain Tumor using Machine Learning
Authors: Moorthy C. , Raghupathy R. , Nithiyameenatchi N. 
Published: March 2023

Abstract
For decades, predicting the presence of gliomas in MRI images and detecting brain tumours at an early stage have been difficult tasks. As the conventional methods are time-consuming and have the problem of low accuracy, there is a need for an automatic, non-invasive diagnosis system for Giloma brain tumours using machine learning techniques. At first, the input MRI images, collected from the hospital, are enhanced using CLAHE, and the skull removal is done. A collection of features, including a modified local binary pattern, a histogram of Gaussian features, intensity features, and a gray-level co-occurrence matrix, are extracted, and the optimised features are selected using sparse PCA. Finally, radial kernel support vector machines are adopted for the accurate classification of normal and Giloma images after being trained with several images. The experimental results of the proposed method depict that the accuracy, sensitivity, and specificity reach 98.5%, 99.3%, and 97.62%, respectively, which is comparably high compared to many existing automatic systems.